Role Overview We are seeking a highly skilled and motivated Senior Data Scientist with deep expertise in Generative AI , Machine Learning , Deep Learning , and advanced Data Analytics . The ideal candidate will have hands-on experience in building, deploying, and maintaining end-to-end ML solutions at scale, preferably within the Telecom domain. You will be part of our AI & Data Science team, working on high-impact projects ranging from customer analytics, network intelligence, churn prediction, to generative AI applications in telco automation and customer experience. Key Responsibilities Design, develop, and deploy advanced machine learning and deep learning models for Telco use cases such as: Network optimization Customer churn prediction Usage pattern modeling Fraud detection GenAI applications (e.g., personalized recommendations, customer service automation) Lead the design and implementation of Generative AI solutions (LLMs, transformers, text-to-text/image models) using tools like OpenAI, Hugging Face, LangChain, etc. Collaborate with cross-functional teams including network, marketing, IT, and business to define AI-driven solutions. Perform exploratory data analysis, feature engineering, model selection, and evaluation using real-world telecom datasets (structured and unstructured). Drive end-to-end ML solution deployment into production (CI/CD pipelines, model monitoring, scalability). Optimize model performance and latency in production, especially for real-time and edge applications. Evaluate and integrate new tools, platforms, and AI frameworks to advance Vi’s data science capabilities. Provide technical mentorship to junior data scientists and data engineers. Required Qualifications & Skills 8+ years of industry experience in Machine Learning, Deep Learning, and Advanced Analytics. Strong hands-on experience with GenAI models and frameworks (e.g., GPT, BERT, Llama, LangChain, RAG pipelines). Proficiency in Python, and libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers, etc. Experience in end-to-end model lifecycle management, from data preprocessing to production deployment (MLOps). Familiarity with cloud platforms like AWS, GCP, or Azure; and ML deployment tools (Docker, Kubernetes, MLflow, FastAPI, etc.). Strong understanding of SQL, big data tools (Spark, Hive), and data pipelines. Excellent problem-solving skills with a strong analytical mindset and business acumen. Prior experience working on Telecom datasets or use cases is a strong plus. Preferred Skills Experience with vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. Exposure to real-time ML inference and streaming data platforms (Kafka, Flink). Knowledge of network analytics, geo-spatial modeling, or customer behavior modeling in a Telco environment. Experience mentoring teams or leading small AI/ML projects. Show more Show less

Role Overview We are looking for a hands-on Data Engineer with 8+ years of experience to build, manage, and scale data pipelines, deploy ML solutions , and enable advanced data visualizations and dashboards for business consumption. The ideal candidate will have a strong engineering mindset, deep understanding of data infrastructure, and prior experience working on self-managed or private cloud (VM-based) deployments. Candidates from premier institutes ( IITs, NITs, or equivalent Tier-1/2 schools ) are strongly preferred. Key Responsibilities Design and build robust, scalable, and secure data pipelines (batch and real-time) to support AI/ML workloads and BI dashboards. Collaborate with data scientists to operationalize ML models, including containerization (Docker), CI/CD pipelines, model serving (FastAPI/Flask), and monitoring. Develop and maintain interactive dashboards using tools such as Plotly Dash, Power BI, or Streamlit to visualize key insights for business stakeholders. Manage deployments and orchestration on Vi’s local private cloud infrastructure (VM-based setups). Work closely with analytics, business, and DevOps teams to ensure reliable data availability and system health. Optimize ETL/ELT workflows for performance and scale across large telecom datasets. Implement data quality checks, governance, and logging/monitoring solutions for all production workloads. Required Qualifications & Skills 8+ years of experience in data engineering, platform development, and/or ML deployment. Prefered B.Tech/M.Tech from Tier-1 or Tier-2 institutes (IITs, NITs, IIITs, BITS, etc.). Strong proficiency in Python, SQL, and data pipeline frameworks (Airflow, Luigi, or similar). Solid experience with containerization (Docker), scripting, and deploying production-grade ML or analytics services. Hands-on experience with dashboarding and visualization tools such as: Power BI / Tableau / Streamlit Custom front-end dashboards (nice to have) Experience working on self-managed VMs, bare-metal servers, or local private clouds (not just public cloud services). Familiarity with ML deployment architectures, REST APIs, and performance tuning. Preferred Skills Experience with Kafka, Spark, or distributed processing systems. Exposure to MLOps tools (MLflow, DVC, Kubeflow). Understanding of telecom data and analytics use cases. Ability to lead and mentor junior engineers or analysts. Show more Show less

Overview We are seeking a skilled Associate Manager - AIOps & MLOps Operations to support and enhance the automation, scalability, and reliability of AI/ML operations across the enterprise. This role requires a solid understanding of AI-driven observability, machine learning pipeline automation, cloud-based AI/ML platforms, and operational excellence. The ideal candidate will assist in deploying AI/ML models, ensuring continuous monitoring, and implementing self-healing automation to improve system performance, minimize downtime, and enhance decision-making with real-time AI-driven insights. Support and maintain AIOps and MLOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Assist in implementing real-time data observability, monitoring, and automation frameworks to enhance data reliability, quality, and operational efficiency. Contribute to developing governance models and execution roadmaps to drive efficiency across data platforms, including Azure, AWS, GCP, and on-prem environments. Ensure seamless integration of CI/CD pipelines, data pipeline automation, and self-healing capabilities across the enterprise. Collaborate with cross-functional teams to support the development and enhancement of next-generation Data & Analytics (D&A) platforms. Assist in managing the people, processes, and technology involved in sustaining Data & Analytics platforms, driving operational excellence and continuous improvement. Support Data & Analytics Technology Transformations by ensuring proactive issue identification and the automation of self-healing capabilities across the PepsiCo Data Estate. Responsibilities Support the implementation of AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting. Assist in deploying Azure-based observability solutions (Azure Monitor, Application Insights, Azure Synapse for log analytics, and Azure Data Explorer) to enhance real-time system performance monitoring. Enable AI-driven anomaly detection and root cause analysis (RCA) by collaborating with data science teams using Azure Machine Learning (Azure ML) and AI-powered log analytics. Contribute to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate to proactively resolve system issues. Support ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI/CD of ML models. Assist in deploying scalable ML models with Azure Kubernetes Service (AKS), Azure Machine Learning Compute, and Azure Container Instances. Automate feature engineering, model versioning, and drift detection using Azure ML Pipelines and MLflow. Optimize ML workflows with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for data preparation and ETL/ELT automation. Implement basic monitoring and explainability for ML models using Azure Responsible AI Dashboard and InterpretML. Collaborate with Data Science, DevOps, CloudOps, and SRE teams to align AIOps/MLOps strategies with enterprise IT goals. Work closely with business stakeholders and IT leadership to implement AI-driven insights and automation to enhance operational decision-making. Track and report AI/ML operational KPIs, such as model accuracy, latency, and infrastructure efficiency. Assist in coordinating with cross-functional teams to maintain system performance and ensure operational resilience. Support the implementation of AI ethics, bias mitigation, and responsible AI practices using Azure Responsible AI Toolkits. Ensure adherence to Azure Information Protection (AIP), Role-Based Access Control (RBAC), and data security policies. Assist in developing risk management strategies for AI-driven operational automation in Azure environments. Prepare and present program updates, risk assessments, and AIOps/MLOps maturity progress to stakeholders as needed. Support efforts to attract and build a diverse, high-performing team to meet current and future business objectives. Help remove barriers to agility and enable the team to adapt quickly to shifting priorities without losing productivity. Contribute to developing the appropriate organizational structure, resource plans, and culture to support business goals. Leverage technical and operational expertise in cloud and high-performance computing to understand business requirements and earn trust with stakeholders. Qualifications 5+ years of technology work experience in a global organization, preferably in CPG or a similar industry. 5+ years of experience in the Data & Analytics field, with exposure to AI/ML operations and cloud-based platforms. 5+ years of experience working within cross-functional IT or data operations teams. 2+ years of experience in a leadership or team coordination role within an operational or support environment. Experience in AI/ML pipeline operations, observability, and automation across platforms such as Azure, AWS, and GCP. Excellent Communication: Ability to convey technical concepts to diverse audiences and empathize with stakeholders while maintaining confidence. Customer-Centric Approach: Strong focus on delivering the right customer experience by advocating for customer needs and ensuring issue resolution. Problem Ownership & Accountability: Proactive mindset to take ownership, drive outcomes, and ensure customer satisfaction. Growth Mindset: Willingness and ability to adapt and learn new technologies and methodologies in a fast-paced, evolving environment. Operational Excellence: Experience in managing and improving large-scale operational services with a focus on scalability and reliability. Site Reliability & Automation: Understanding of SRE principles, automated remediation, and operational efficiencies. Cross-Functional Collaboration: Ability to build strong relationships with internal and external stakeholders through trust and collaboration. Familiarity with CI/CD processes, data pipeline management, and self-healing automation frameworks. Strong understanding of data acquisition, data catalogs, data standards, and data management tools. Knowledge of master data management concepts, data governance, and analytics. Show more Show less

Overview We are seeking a skilled Associate Manager - AIOps & MLOps Operations to support and enhance the automation, scalability, and reliability of AI/ML operations across the enterprise. This role requires a solid understanding of AI-driven observability, machine learning pipeline automation, cloud-based AI/ML platforms, and operational excellence. The ideal candidate will assist in deploying AI/ML models, ensuring continuous monitoring, and implementing self-healing automation to improve system performance, minimize downtime, and enhance decision-making with real-time AI-driven insights. Support and maintain AIOps and MLOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Assist in implementing real-time data observability, monitoring, and automation frameworks to enhance data reliability, quality, and operational efficiency. Contribute to developing governance models and execution roadmaps to drive efficiency across data platforms, including Azure, AWS, GCP, and on-prem environments. Ensure seamless integration of CI/CD pipelines, data pipeline automation, and self-healing capabilities across the enterprise. Collaborate with cross-functional teams to support the development and enhancement of next-generation Data & Analytics (D&A) platforms. Assist in managing the people, processes, and technology involved in sustaining Data & Analytics platforms, driving operational excellence and continuous improvement. Support Data & Analytics Technology Transformations by ensuring proactive issue identification and the automation of self-healing capabilities across the PepsiCo Data Estate. Responsibilities Support the implementation of AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting. Assist in deploying Azure-based observability solutions (Azure Monitor, Application Insights, Azure Synapse for log analytics, and Azure Data Explorer) to enhance real-time system performance monitoring. Enable AI-driven anomaly detection and root cause analysis (RCA) by collaborating with data science teams using Azure Machine Learning (Azure ML) and AI-powered log analytics. Contribute to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate to proactively resolve system issues. Support ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI/CD of ML models. Assist in deploying scalable ML models with Azure Kubernetes Service (AKS), Azure Machine Learning Compute, and Azure Container Instances. Automate feature engineering, model versioning, and drift detection using Azure ML Pipelines and MLflow. Optimize ML workflows with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for data preparation and ETL/ELT automation. Implement basic monitoring and explainability for ML models using Azure Responsible AI Dashboard and InterpretML. Collaborate with Data Science, DevOps, CloudOps, and SRE teams to align AIOps/MLOps strategies with enterprise IT goals. Work closely with business stakeholders and IT leadership to implement AI-driven insights and automation to enhance operational decision-making. Track and report AI/ML operational KPIs, such as model accuracy, latency, and infrastructure efficiency. Assist in coordinating with cross-functional teams to maintain system performance and ensure operational resilience. Support the implementation of AI ethics, bias mitigation, and responsible AI practices using Azure Responsible AI Toolkits. Ensure adherence to Azure Information Protection (AIP), Role-Based Access Control (RBAC), and data security policies. Assist in developing risk management strategies for AI-driven operational automation in Azure environments. Prepare and present program updates, risk assessments, and AIOps/MLOps maturity progress to stakeholders as needed. Support efforts to attract and build a diverse, high-performing team to meet current and future business objectives. Help remove barriers to agility and enable the team to adapt quickly to shifting priorities without losing productivity. Contribute to developing the appropriate organizational structure, resource plans, and culture to support business goals. Leverage technical and operational expertise in cloud and high-performance computing to understand business requirements and earn trust with stakeholders. Qualifications 5+ years of technology work experience in a global organization, preferably in CPG or a similar industry. 5+ years of experience in the Data & Analytics field, with exposure to AI/ML operations and cloud-based platforms. 5+ years of experience working within cross-functional IT or data operations teams. 2+ years of experience in a leadership or team coordination role within an operational or support environment. Experience in AI/ML pipeline operations, observability, and automation across platforms such as Azure, AWS, and GCP. Excellent Communication: Ability to convey technical concepts to diverse audiences and empathize with stakeholders while maintaining confidence. Customer-Centric Approach: Strong focus on delivering the right customer experience by advocating for customer needs and ensuring issue resolution. Problem Ownership & Accountability: Proactive mindset to take ownership, drive outcomes, and ensure customer satisfaction. Growth Mindset: Willingness and ability to adapt and learn new technologies and methodologies in a fast-paced, evolving environment. Operational Excellence: Experience in managing and improving large-scale operational services with a focus on scalability and reliability. Site Reliability & Automation: Understanding of SRE principles, automated remediation, and operational efficiencies. Cross-Functional Collaboration: Ability to build strong relationships with internal and external stakeholders through trust and collaboration. Familiarity with CI/CD processes, data pipeline management, and self-healing automation frameworks. Strong understanding of data acquisition, data catalogs, data standards, and data management tools. Knowledge of master data management concepts, data governance, and analytics. Show more Show less

Overview We are seeking a skilled Associate Manager - AIOps & MLOps Operations to support and enhance the automation, scalability, and reliability of AI/ML operations across the enterprise. This role requires a solid understanding of AI-driven observability, machine learning pipeline automation, cloud-based AI/ML platforms, and operational excellence. The ideal candidate will assist in deploying AI/ML models, ensuring continuous monitoring, and implementing self-healing automation to improve system performance, minimize downtime, and enhance decision-making with real-time AI-driven insights. Support and maintain AIOps and MLOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Assist in implementing real-time data observability, monitoring, and automation frameworks to enhance data reliability, quality, and operational efficiency. Contribute to developing governance models and execution roadmaps to drive efficiency across data platforms, including Azure, AWS, GCP, and on-prem environments. Ensure seamless integration of CI/CD pipelines, data pipeline automation, and self-healing capabilities across the enterprise. Collaborate with cross-functional teams to support the development and enhancement of next-generation Data & Analytics (D&A) platforms. Assist in managing the people, processes, and technology involved in sustaining Data & Analytics platforms, driving operational excellence and continuous improvement. Support Data & Analytics Technology Transformations by ensuring proactive issue identification and the automation of self-healing capabilities across the PepsiCo Data Estate. Responsibilities Support the implementation of AIOps strategies for automating IT operations using Azure Monitor, Azure Log Analytics, and AI-driven alerting. Assist in deploying Azure-based observability solutions (Azure Monitor, Application Insights, Azure Synapse for log analytics, and Azure Data Explorer) to enhance real-time system performance monitoring. Enable AI-driven anomaly detection and root cause analysis (RCA) by collaborating with data science teams using Azure Machine Learning (Azure ML) and AI-powered log analytics. Contribute to developing self-healing and auto-remediation mechanisms using Azure Logic Apps, Azure Functions, and Power Automate to proactively resolve system issues. Support ML lifecycle automation using Azure ML, Azure DevOps, and Azure Pipelines for CI/CD of ML models. Assist in deploying scalable ML models with Azure Kubernetes Service (AKS), Azure Machine Learning Compute, and Azure Container Instances. Automate feature engineering, model versioning, and drift detection using Azure ML Pipelines and MLflow. Optimize ML workflows with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics for data preparation and ETL/ELT automation. Implement basic monitoring and explainability for ML models using Azure Responsible AI Dashboard and InterpretML. Collaborate with Data Science, DevOps, CloudOps, and SRE teams to align AIOps/MLOps strategies with enterprise IT goals. Work closely with business stakeholders and IT leadership to implement AI-driven insights and automation to enhance operational decision-making. Track and report AI/ML operational KPIs, such as model accuracy, latency, and infrastructure efficiency. Assist in coordinating with cross-functional teams to maintain system performance and ensure operational resilience. Support the implementation of AI ethics, bias mitigation, and responsible AI practices using Azure Responsible AI Toolkits. Ensure adherence to Azure Information Protection (AIP), Role-Based Access Control (RBAC), and data security policies. Assist in developing risk management strategies for AI-driven operational automation in Azure environments. Prepare and present program updates, risk assessments, and AIOps/MLOps maturity progress to stakeholders as needed. Support efforts to attract and build a diverse, high-performing team to meet current and future business objectives. Help remove barriers to agility and enable the team to adapt quickly to shifting priorities without losing productivity. Contribute to developing the appropriate organizational structure, resource plans, and culture to support business goals. Leverage technical and operational expertise in cloud and high-performance computing to understand business requirements and earn trust with stakeholders. Qualifications 5+ years of technology work experience in a global organization, preferably in CPG or a similar industry. 5+ years of experience in the Data & Analytics field, with exposure to AI/ML operations and cloud-based platforms. 5+ years of experience working within cross-functional IT or data operations teams. 2+ years of experience in a leadership or team coordination role within an operational or support environment. Experience in AI/ML pipeline operations, observability, and automation across platforms such as Azure, AWS, and GCP. Excellent Communication: Ability to convey technical concepts to diverse audiences and empathize with stakeholders while maintaining confidence. Customer-Centric Approach: Strong focus on delivering the right customer experience by advocating for customer needs and ensuring issue resolution. Problem Ownership & Accountability: Proactive mindset to take ownership, drive outcomes, and ensure customer satisfaction. Growth Mindset: Willingness and ability to adapt and learn new technologies and methodologies in a fast-paced, evolving environment. Operational Excellence: Experience in managing and improving large-scale operational services with a focus on scalability and reliability. Site Reliability & Automation: Understanding of SRE principles, automated remediation, and operational efficiencies. Cross-Functional Collaboration: Ability to build strong relationships with internal and external stakeholders through trust and collaboration. Familiarity with CI/CD processes, data pipeline management, and self-healing automation frameworks. Strong understanding of data acquisition, data catalogs, data standards, and data management tools. Knowledge of master data management concepts, data governance, and analytics. Show more Show less

P-375 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Databricks Mosaic AI offers a unique data-centric approach to building enterprise-quality, Machine Learning and Generative AI solutions, enabling organizations to securely and cost-effectively own and host ML and Generative AI models, augmented or trained with their enterprise data. And we're only getting started in Bengaluru , India - and currently in the process of setting up 10 new teams from scratch ! As a Staff Software Engineer at Databricks India, you can get to work across : Backend DDS (Distributed Data Systems) The Impact You'll Have Our Backend teams span many domains across our essential service platforms. For instance, you might work on challenges such as: Problems that span from product to infrastructure including: distributed systems, at-scale service architecture and monitoring, workflow orchestration, and developer experience. Deliver reliable and high performance services and client libraries for storing and accessing humongous amount of data on cloud storage backends, e.g., AWS S3, Azure Blob Store. Build reliable, scalable services, e.g. Scala, Kubernetes, and data pipelines, e.g. Apache Spark™, Databricks, to power the pricing infrastructure that serves millions of cluster-hours per day and develop product features that empower customers to easily view and control platform usage. Our DDS team spans across: Apache Spark™ Data Plane Storage Delta Lake Delta Pipelines Performance Engineering What We Look For BS (or higher) in Computer Science, or a related field 10+ years of production level experience in one of: Python, Java, Scala, C++, or similar language. Experience developing large-scale distributed systems from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook. Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Show more Show less

What makes Techjays an inspiring place to work: At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals who have honed their skills at leading companies such as Google, Akamai, NetApp, ADP, Cognizant Consulting, and Capgemini. With engineering teams across the globe, we deliver tailored AI software and services to clients ranging from startups to large-scale enterprises. Be part of a company that’s pushing the boundaries of digital transformation. At Techjays, you’ll work on exciting projects that redefine industries, innovate with the latest technologies, and contribute to solutions that make a real-world impact. Join us on our journey to shape the future with AI. We are looking for a mid-level AI Implementation Engineer with a strong Python background to join our AI initiatives team. In this role, you will help design and develop production-ready systems that combine information retrieval, vector databases, and large language models (LLMs) into scalable Retrieval-Augmented Generation (RAG) pipelines. You’ll work closely with AI researchers, backend engineers, and data teams to bring generative AI use cases to life across multiple domains. Key Responsibilities: Develop and maintain scalable Python services that implement AI-powered retrieval and generation workflows. Build and optimize vector-based retrieval pipelines using tools like FAISS , Pinecone , or Weaviate . Integrate LLMs via APIs (e.g., OpenAI, Hugging Face) using orchestration frameworks such as LangChain , LlamaIndex , etc. Collaborate on system architecture, API design, and data flow to support RAG systems. Monitor, test, and improve the performance and accuracy of AI features in production. Work in cross-functional teams with product, data, and ML stakeholders to deploy AI solutions quickly and responsibly. Requirements: 3–5 years of hands-on experience in Python development, with focus on backend or data-intensive systems. Experience with information retrieval concepts and tools (e.g., Elasticsearch, vector search engines). Familiarity with LLM integration or orchestration tools (LangChain, LlamaIndex, etc.). Working knowledge of RESTful API development, microservices, and containerization (Docker). Solid software engineering practices including Git, testing, and CI/CD pipelines. Nice to have: Exposure to prompt engineering or fine-tuning LLMs. Experience deploying cloud-based AI applications (AWS, GCP, or Azure). Familiarity with document ingestion pipelines and unstructured data processing. Understanding of MLOps tools and practices (e.g., MLflow, Airflow). What we offer: Best-in-class packages. Paid holidays and flexible time-off policies. Casual dress code and a flexible working environment. Opportunities for professional development in an engaging, fast-paced environment. Medical insurance covering self and family up to 4 lakhs per person. Diverse and multicultural work environment. Be part of an innovation-driven culture with ample support and resources to succeed. Show more Show less

About Agoda Agoda is an online travel booking platform for accommodations, flights, and more. We build and deploy cutting-edge technology that connects travelers with a global network of 4.7M hotels and holiday properties worldwide, plus flights, activities, and more . Based in Asia and part of Booking Holdings, our 7,100+ employees representing 95+ nationalities in 27 markets foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enhancing the ability for our customers to experience the world. Our Purpose – Bridging the World Through Travel We believe travel allows people to enjoy, learn and experience more of the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding and happiness. We are a skillful, driven and diverse team from across the globe, united by a passion to make an impact. Harnessing our innovative technologies and strong partnerships, we aim to make travel easy and rewarding for everyone. Get to Know our Team In Agoda’s Back-End Engineering department, we build scalable, fault-tolerant systems and APIs that host our core business logic. Our systems cover all major areas of our business: inventory and pricing, product information, customer data, communications, partner data, booking systems, payments, and more. We employ state-of-the-art CI/CD and testing techniques to ensure everything works without downtime. Our systems are self-healing, responding gracefully to extreme loads or unexpected input. We use modern languages like Kotlin and Scala, Data technologies Kafka, Spark, MLflow, Kubeflow, VastStorage, StarRocks and agile development practices. Most importantly, we hire great people from around the world and empower them to be successful. The Opportunity Agoda Platform team is looking for developers to work on mission-critical systems that serve millions of users daily. You will have the chance to work on innovative projects, using cutting-edge technologies, and make a significant impact on our business and the travel industry. What You’ll Need To Succeed 5+ years of experience developing performance-critical applications in a production environment using Scala, Java, Kotlin, C#, Go or relevant modern programming languages. Strong RDBMS knowledge (SQL Server, Oracle, MySQL, or other). Ability to design and implement scalable architectures Deeply involved in hands-on coding, developing and maintaining high-quality software solutions on a daily basis Good command of the English language. Engages in cross-team collaborations to ensure cohesive solutions Implement advanced CI/CD pipelines and robust testing strategies to ensure seamless integration, deployment, and high code quality. Passion for software development and continuous improvement of your knowledge and skills. It’s Great if You Have Knowledge in NoSQL, Queueing systems (Kafka, RabbitMQ, ActiveMQ, MSMQ), and Play framework. #newdelhi #Pune #Hyderabad #Bangalore #Mumbai #Bengaluru #Chennai #Kolkata #Lucknow #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #mexico #sydney #melbourne #toronto #vancouver #shanghai #beijing #shenzhen#estonia #paris #hongkong #budapest #jakarta #bali #kualalumpur #dublin #berlin #telaviv #milan #rome #tokyo #osaka #amsterdam #oslo #manila #warsaw #krakow #moscow #saintpetersburg #capetown #johannesburg #seoul #barcelona #madrid #stockholm #zurich #taipei #bangkok #chiangmai #phuket #istanbul #london #manchester #edinburgh #kiev #hcmc #hanoi #hochimin #wroclaw #poznan #katowice #rio #salvador #dhaka #islamabad #IT #ENG #4 Equal Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics. We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy . Disclaimer We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee. Show more Show less

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge. Job Description: The Future Begins Here: At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet. Bengaluru, the city, which is India’s epicenter of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement. At Takeda’s ICC we Unite in Diversity : Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team. About The Role We are seeking an innovative and skilled Principal AI/ML Engineer with a strong focus on designing and deploying scalable machine learning solutions. This role requires a strategic thinker who can architect production-ready solutions, collaborate closely with cross-functional teams, and ensure adherence to Takeda’s technical standards through participation in the Architecture Council. The ideal candidate has extensive experience in operationalizing ML models, MLOps workflows, and building systems aligned with healthcare standards. By leveraging cutting-edge machine learning and engineering principles, this role supports Takeda’s global mission of delivering transformative therapies to patients worldwide. How You Will Contribute Architect scalable and secure machine learning systems that integrate with Takeda’s enterprise platforms, including R&D, manufacturing, and clinical trial operations. Design and implement pipelines for model deployment, monitoring, and retraining using advanced MLOps tools such as MLflow, Airflow, and Databricks. Operationalize AI/ML models for production environments, ensuring efficient CI/CD workflows and reproducibility. Collaborate with Takeda’s Architecture Council to propose and refine AI/ML system designs, balancing technical excellence with strategic alignment. Implement monitoring systems to track model performance (accuracy, latency, drift) in a production setting, using tools such as Prometheus or Grafana. Ensure compliance with industry regulations (e.g., GxP, GDPR) and Takeda’s ethical AI standards in system deployment. Identify use cases where machine learning can deliver business value, and propose enterprise-level solutions aligned to strategic goals. Work with Databricks tools and platforms for model management and data workflows, optimizing solutions for scalability. Manage and document the lifecycle of deployed ML systems, including versioning, updates, and data flow architecture. Drive adoption of standardized architecture and MLOps frameworks across disparate teams within Takeda. Skills And Qualifications Education Bachelors or Master’s or Ph.D. in Computer Science, Software Engineering, Data Science, or related field. Experience At least 6-8 years of experience in machine learning system architecture, deployment, and MLOps, with a significant focus on operationalizing ML at scale. Proven track record in designing and advocating ML/AI solutions within enterprise architecture frameworks and council-level decision-making. Technical Skills Proficiency in deploying and managing machine learning pipelines using MLOps tools like MLflow, Airflow, Databricks, or Clear ML. Strong programming skills in Python and experience with machine learning libraries such as Scikit-learn, XGBoost, LightGBM, and TensorFlow. Deep understanding of CI/CD pipelines and tools (e.g., Jenkins, GitHub Actions) for automated model deployment. Familiarity with Databricks tools and services for scalable data workflows and model management. Expertise in building robust observability and monitoring systems to track ML systems in production. Hands-on experience with classical machine learning techniques, such as random forests, decision trees, SVMs, and clustering methods. Knowledge of infrastructure-as-code tools like Terraform or CloudFormation to enable automated deployments. Experience in handling regulatory considerations and compliance in healthcare AI/ML implementations (e.g., GxP, GDPR). Soft Skills Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills for influencing technical and non-technical stakeholders. Leadership ability to mentor teams and drive architecture-standardization initiatives. Ability to manage projects independently and advocate for AI/ML adoption across Takeda. Preferred Qualifications Real-world experience operationalizing machine learning for pharmaceutical domains, including drug discovery, patient stratification, and manufacturing process optimization. Familiarity with ethical AI principles and frameworks, aligned with FAIR data standards in healthcare. Publications or contributions to AI research or MLOps tooling communities. WHAT TAKEDA ICC INDIA CAN OFFER YOU: Takeda is certified as a Top Employer, not only in India, but also globally. No investment we make pays greater dividends than taking good care of our people. At Takeda, you take the lead on building and shaping your own career. Joining the ICC in Bengaluru will give you access to high-end technology, continuous training and a diverse and inclusive network of colleagues who will support your career growth. BENEFITS: It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are Competitive Salary + Performance Annual Bonus Flexible work environment, including hybrid working Comprehensive Healthcare Insurance Plans for self, spouse, and children Group Term Life Insurance and Group Accident Insurance programs Health & Wellness programs including annual health screening, weekly health sessions for employees. Employee Assistance Program 5 days of leave every year for Voluntary Service in additional to Humanitarian Leaves Broad Variety of learning platforms Diversity, Equity, and Inclusion Programs No Meeting Days Reimbursements – Home Internet & Mobile Phone Employee Referral Program Leaves – Paternity Leave (4 Weeks), Maternity Leave (up to 26 weeks), Bereavement Leave (5 days) ABOUT ICC IN TAKEDA: Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day. As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization. Locations: IND - Bengaluru Worker Type: Employee Worker Sub-Type: Regular Time Type: Full time Show more Show less

About Us All people need connectivity. The Rakuten Group is reinventing telecom by greatly reducing cost, rewarding big users not penalizing them, empowering more people and leading the human centric AI future. The mission is to connect everybody and enable all to be. Rakuten. Telecom Invented. Job Description Job Title: Senior AI/ML Engineer (Generative AI & ML Ops) Minimum 8+ years of experience in AI/ML development. Location : Bangalore Required Skills And Expertise AI/ML Strategy and Leadership: Define the AI/ML strategy and roadmap aligned with the product vision. Identify and prioritize AI/ML use cases, including classical ML, Generative AI, and Agentic AI, relevant to our product offerings. Build and lead a high-performing AI/ML team by mentoring and upskilling existing non-AI/ML team members. Stay updated with the latest advancements in AI/ML, generative AI, Agentic AI and ML Ops, and apply them to solve business problems. AI/ML Development: Proficient in Python programming and libraries like NumPy, Pandas, Scikit-learn, and Matplotlib. Strong understanding of machine learning algorithms, deep learning architectures, and generative AI models. Design, develop, and deploy classical machine learning models, including supervised, unsupervised, and reinforcement learningtechniques. Hands on Experience in AI/ML Framework like: Scikit-learn, XG Boost, TensorFlow, Py Torch, Keras, Hugging Face, OpenAI APIs (e.g., GPT models). Experience with feature engineering, model evaluation, and hyperparameter tuning. Experience with Lang Chain modules, including Chains, Memory, Tools, and Agents. Build and fine-tune generative AI models (e.g., GPT, DALL-E, Stable Diffusion) for specific use cases. Must Have Exp. in any Agentic AI framework. Leverage LLMs (e.g., GPT, Claude, LLaMA) and multi-modal models to build intelligent agents that can interact with users and systems. Design and develop autonomous AI agents capable of reasoning, planning, and executing tasks in dynamic environments. Implement prompt engineering and fine-tuning of LLMs to optimize agent behaviour for specific tasks. Optimize models for performance, scalability, and cost-efficiency. Job Requirement MLOps And DevOps For AI/ML Establish and maintain an end-to-end MLOps pipeline for model development, deployment, monitoring, and retraining. Automate model training, testing, and deployment workflows using CI/CD pipelines. Implement robust version control for datasets, models, and code. Monitor model performance in production and implement feedback loops for continuous improvement. Proficiency in MLOps tools and platforms such as MLflow, Kubeflow, TFX, SageMaker. Familiarity with CI/CD tools like Jenkins, GitHub Actions, or GitLab CI for AI/ML workflows. Expertise in deploying models on cloud platforms (AWS, Azure, GCP) Show more Show less

About Agoda Agoda is an online travel booking platform for accommodations, flights, and more. We build and deploy cutting-edge technology that connects travelers with a global network of 4.7M hotels and holiday properties worldwide, plus flights, activities, and more . Based in Asia and part of Booking Holdings, our 7,100+ employees representing 95+ nationalities in 27 markets foster a work environment rich in diversity, creativity, and collaboration. We innovate through a culture of experimentation and ownership, enhancing the ability for our customers to experience the world. Our Purpose – Bridging the World Through Travel We believe travel allows people to enjoy, learn and experience more of the amazing world we live in. It brings individuals and cultures closer together, fostering empathy, understanding and happiness. We are a skillful, driven and diverse team from across the globe, united by a passion to make an impact. Harnessing our innovative technologies and strong partnerships, we aim to make travel easy and rewarding for everyone. Get to Know our Team In Agoda’s Back-End Engineering department, we build scalable, fault-tolerant systems and APIs that host our core business logic. Our systems cover all major areas of our business: inventory and pricing, product information, customer data, communications, partner data, booking systems, payments, and more. We employ state-of-the-art CI/CD and testing techniques to ensure everything works without downtime. Our systems are self-healing, responding gracefully to extreme loads or unexpected input. We use modern languages like Kotlin and Scala, Data technologies Kafka, Spark, MLflow, Kubeflow, VastStorage, StarRocks and agile development practices. Most importantly, we hire great people from around the world and empower them to be successful. The Opportunity Agoda Platform team is looking for developers to work on mission-critical systems that serve millions of users daily. You will have the chance to work on innovative projects, using cutting-edge technologies, and make a significant impact on our business and the travel industry. What You’ll Need To Succeed 5+ years of experience developing performance-critical applications in a production environment using Scala, Java, Kotlin, C#, Go or relevant modern programming languages. Strong RDBMS knowledge (SQL Server, Oracle, MySQL, or other). Ability to design and implement scalable architectures Deeply involved in hands-on coding, developing and maintaining high-quality software solutions on a daily basis Good command of the English language. Engages in cross-team collaborations to ensure cohesive solutions Implement advanced CI/CD pipelines and robust testing strategies to ensure seamless integration, deployment, and high code quality. Passion for software development and continuous improvement of your knowledge and skills. It’s Great if You Have Knowledge in NoSQL, Queueing systems (Kafka, RabbitMQ, ActiveMQ, MSMQ), and Play framework. #newdelhi #Pune #Hyderabad #Bangalore #Mumbai #Bengaluru #Chennai #Kolkata #Lucknow #sanfrancisco #sanjose #losangeles #sandiego #oakland #denver #miami #orlando #atlanta #chicago #boston #detroit #newyork #portland #mexico #sydney #melbourne #toronto #vancouver #shanghai #beijing #shenzhen#estonia #paris #hongkong #budapest #jakarta #bali #kualalumpur #dublin #berlin #telaviv #milan #rome #tokyo #osaka #amsterdam #oslo #manila #warsaw #krakow #moscow #saintpetersburg #capetown #johannesburg #seoul #barcelona #madrid #stockholm #zurich #taipei #bangkok #chiangmai #phuket #istanbul #london #manchester #edinburgh #kiev #hcmc #hanoi #hochimin #wroclaw #poznan #katowice #rio #salvador #dhaka #islamabad #IT #ENG #4 Equal Opportunity Employer At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics. We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy . Disclaimer We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee. Show more Show less

Python 4+ years of experience in Machine learning/Data Science, and Python. 4+ years of experience in NLP/GenAI/LLMs. Report to CES Innovation Lead and work under the supervision of the CES AI Science Lead. Work with ESG stakeholders to understand business problems and connect these problems with solvable data science solutions. Audit the different text data assets of the CES department and determine how to analyze these data assets for insights. Prepare high-quality training data with appropriate coverage of the ESG business domain. Apply and implement the latest natural language processing (NLP) research and approaches to solve business problems. Apply Large Language Models (both open source and managed versions) to build robust multiagentic retrieval augmented generation (RAG) pipelines. Stay current with the latest research advancements in the field and apply innovative solutions to complex language processing challenges. Required Skills (Mandatory) At least four years work experience in machine learning, Generative AI (GenAI) with experience in at least two of the following deep learning frameworks: SciKit-Learn, TensorFlow, MLflow, PyTorch, etc. At least four years of experience in NLP and Large Language Models (LLMs) with a comprehensive understanding of the underlying theories and principles including expertise in areas such as tokenization, embedding techniques, sequence-to-sequence models, attention mechanisms, and transformer architectures. In-depth understanding of text analytics and NLP concepts such as lemmatization, word segmentation, part-of-speech, tagging, stemming, Named-Entity Recognition, word2Vec, Doc2Vec, etc. Proficient in Machine Translation and Optical Character Recognition (OCR) for complex document processing (PDF, Word Documents, Scanned Documents). Expertise in Python with strong object-oriented design and programming skills with familiarity with CI/CD concepts. Proficient with parallel processing APIs such as Apache Spark and PySpark. Excellent problem-solving and analytical skills Show more Show less

India - Hyderabad JOB ID: R-216752 ADDITIONAL LOCATIONS: India - Hyderabad WORK LOCATION TYPE: On Site DATE POSTED: Jun. 06, 2025 CATEGORY: Information Systems Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. What you will do Let’s do this. Let’s change the world. We are seeking a highly skilled Machine Learning Engineer with a strong MLOps background to join our team. You will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. Roles & Responsibilities: Collaborate with data scientists to develop, train, and evaluate machine learning models. Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct A/B testing and experimentation to optimize model performance. Work closely with data scientists, engineers, and product teams to deliver ML solutions. Guide and mentor junior engineers in the team Stay updated with the latest trends and advancements What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate degree and 2 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Master’s degree and 8 to 10 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Bachelor’s degree and 10 to 14 years of Computer Science, Statistics, and Data Science, Machine Learning experience OR Diploma and 14 to 18 years of years of Computer Science, Statistics, and Data Science, Machine Learning experience Preferred Qualifications: Must-Have Skills: Strong foundation in machine learning algorithms and techniques Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow); Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills; Ability to learn quickly; Excellent communication and interpersonal skills Good-to-Have Skills: Experience with big data technologies (e.g., Spark), and performance tuning in query and data processing Experience with data engineering and pipeline development Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Knowledge of NLP techniques for text analysis and sentiment analysis Experience in analyzing time-series data for forecasting and trend analysis Familiar with AWS, Azure, or Google Cloud; Familiar with Databricks platform for data analytics and MLOps Professional Certifications Cloud Computing and Databricks certificate preferred Soft Skills: Excellent analytical and fixing skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Company Overview Milestone Technologies is a global IT managed services firm that partners with organizations to scale their technology, infrastructure and services to drive specific business outcomes such as digital transformation, innovation, and operational agility. Milestone is focused on building an employee-first, performance-based culture and for over 25 years, we have a demonstrated history of supporting category-defining enterprise clients that are growing ahead of the market. The company specializes in providing solutions across Application Services and Consulting, Digital Product Engineering, Digital Workplace Services, Private Cloud Services, AI/Automation, and ServiceNow. Milestone culture is built to provide a collaborative, inclusive environment that supports employees and empowers them to reach their full potential. Our seasoned professionals deliver services based on Milestone’s best practices and service delivery framework. By leveraging our vast knowledge base to execute initiatives, we deliver both short-term and long-term value to our clients and apply continuous service improvement to deliver transformational benefits to IT. With Intelligent Automation, Milestone helps businesses further accelerate their IT transformation. The result is a sharper focus on business objectives and a dramatic improvement in employee productivity. Through our key technology partnerships and our people-first approach, Milestone continues to deliver industry-leading innovation to our clients. With more than 3,000 employees serving over 200 companies worldwide, we are following our mission of revolutionizing the way IT is deployed. Job Overview Job Summary: We are seeking a highly experienced and visionary Databricks Data Architect with over 14 years in data engineering and architecture, including deep hands-on experience in designing and scaling Lakehouse architectures using Databricks . The ideal candidate will possess deep expertise across data modeling, data governance, real-time and batch processing, and cloud-native analytics using the Databricks platform. You will lead the strategy, design, and implementation of modern data architecture to drive enterprise-wide data initiatives and maximize the value from the Databricks platform. Key Responsibilities Lead the architecture, design, and implementation of scalable and secure Lakehouse solutions using Databricks and Delta Lake. Define and implement data modeling best practices, including medallion architecture (bronze/silver/gold layers). Champion data quality and governance frameworks leveraging Databricks Unity Catalog for metadata, lineage, access control, and auditing. Architect real-time and batch data ingestion pipelines using Apache Spark Structured Streaming, Auto Loader, and Delta Live Tables (DLT). Develop reusable templates, workflows, and libraries for data ingestion, transformation, and consumption across various domains. Collaborate with enterprise data governance and security teams to ensure compliance with regulatory and organizational data standards. Promote self-service analytics and data democratization by enabling business users through Databricks SQL and Power BI/Tableau integrations. Partner with Data Scientists and ML Engineers to enable ML workflows using MLflow, Feature Store, and Databricks Model Serving. Provide architectural leadership for enterprise data platforms, including performance optimization, cost governance, and CI/CD automation in Databricks. Define and drive the adoption of DevOps/MLOps best practices on Databricks using Databricks Repos, Git, Jobs, and Terraform. Mentor and lead engineering teams on modern data platform practices, Spark performance tuning, and efficient Delta Lake optimizations (Z-ordering, OPTIMIZE, VACUUM, etc.). Technical Skills 10+ years in Data Warehousing, Data Architecture, and Enterprise ETL design. 5+ years hands-on experience with Databricks on Azure/AWS/GCP, including advanced Apache Spark and Delta Lake. Strong command of SQL, PySpark, and Spark SQL for large-scale data transformation. Proficiency with Databricks Unity Catalog, Delta Live Tables, Autoloader, DBFS, Jobs, and Workflows. Hands-on experience with Databricks SQL and integration with BI tools (Power BI, Tableau, etc.). Experience implementing CI/CD on Databricks, using tools like Git, Azure DevOps, Terraform, and Databricks Repos. Proficient with streaming architecture using Spark Structured Streaming, Kafka, or Event Hubs/Kinesis. Understanding of ML lifecycle management with MLflow, and experience in deploying MLOps solutions on Databricks. Familiarity with cloud object stores (e.g., AWS S3, Azure Data Lake Gen2) and data lake architectures. Exposure to data cataloging and metadata management using Unity Catalog or third-party tools. Knowledge of orchestration tools like Airflow, Databricks Workflows, or Azure Data Factory. Experience with Docker/Kubernetes for containerization (optional, for cross-platform knowledge). Preferred Certifications (a Plus) Databricks Certified Data Engineer Associate/Professional Databricks Certified Lakehouse Architect Microsoft Certified: Azure Data Engineer / Azure Solutions Architect AWS Certified Data Analytics – Specialty Google Professional Data Engineer Compensation Estimated Pay Range: Exact compensation and offers of employment are dependent on circumstances of each case and will be determined based on job-related knowledge, skills, experience, licenses or certifications, and location. Our Commitment to Diversity & Inclusion At Milestone we strive to create a workplace that reflects the communities we serve and work with, where we all feel empowered to bring our full, authentic selves to work. We know creating a diverse and inclusive culture that champions equity and belonging is not only the right thing to do for our employees but is also critical to our continued success. Milestone Technologies provides equal employment opportunity for all applicants and employees. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, gender, gender identity, marital status, age, disability, veteran status, sexual orientation, national origin, or any other category protected by applicable federal and state law, or local ordinance. Milestone also makes reasonable accommodations for disabled applicants and employees. We welcome the unique background, culture, experiences, knowledge, innovation, self-expression and perspectives you can bring to our global community. Our recruitment team is looking forward to meeting you. Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Key Responsibilities: Develop and implement machine learning models and algorithms for various business use cases. Preprocess and analyze structured and unstructured data (text, image, video, etc.). Collaborate with cross-functional teams to integrate AI models into production systems. Conduct model validation, tuning, and performance evaluation. Stay up-to-date with the latest research and trends in AI and ML. Document processes and maintain clear version control using tools like Git. Required Skills & Qualifications: Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field. 1–2 years of hands-on experience in machine learning, deep learning, or AI projects. Proficiency in Python and libraries such as TensorFlow, PyTorch, Scikit-learn, or Keras. Experience with data preprocessing, feature engineering, and model evaluation. Familiarity with tools like Jupyter Notebook, Pandas, NumPy, and visualization libraries (e.g., Matplotlib, Seaborn). Understanding of REST APIs and deploying models via Flask/FastAPI or similar frameworks. Exposure to cloud platforms (AWS, GCP, Azure) is a plus. Preferred Qualifications: Experience with NLP, Computer Vision, or Time Series forecasting. Knowledge of databases (SQL/NoSQL) and data pipelines. Contributions to open-source or AI/ML competitions (Kaggle, etc.). Familiarity with MLOps tools (e.g., MLflow, Docker, Kubernetes) is a bonus. Soft Skills: Strong analytical and problem-solving abilities. Effective communication and collaboration skills. Curious, self-driven, and eager to learn. What We Offer: Competitive salary and benefits. Mentorship and opportunities for skill development. A collaborative and dynamic work environment. Job Type: Full-time Pay: ₹400,000.00 - ₹800,000.00 per year Schedule: Day shift Supplemental Pay: Yearly bonus Work Location: In person

About the Role We are seeking a highly skilled and versatile Senior AI Engineer with over 5 years of hands-on experience to join our client’s team in Pune. This role focuses on designing, developing, and deploying cutting-edge AI and machine learning solutions for high-scale, high-concurrency applications where security, scalability, and performance are paramount. You will work closely with cross-functional teams, including data scientists, DevOps engineers, security specialists, and business stakeholders, to deliver robust AI solutions that drive measurable business impact in dynamic, large-scale environments. Key Responsibilities Architect, develop, and deploy advanced machine learning and deep learning models across domains like NLP, computer vision, predictive analytics, or reinforcement learning, ensuring scalability and performance under high-traffic conditions. Preprocess, clean, and analyze large-scale structured and unstructured datasets using advanced statistical, ML, and big data techniques. Collaborate with data engineering and DevOps teams to integrate AI/ML models into production-grade pipelines, ensuring seamless operation under high concurrency. Optimize models for latency, throughput, accuracy, and resource efficiency, leveraging distributed computing and parallel processing where necessary. Implement robust security measures, including data encryption, secure model deployment, and adherence to compliance standards (e.g., GDPR, CCPA). Partner with client-side technical teams to translate complex business requirements into scalable, secure AI-driven solutions. Stay at the forefront of AI/ML advancements, experimenting with emerging tools, frameworks, and techniques (e.g., generative AI, federated learning, or AutoML). Write clean, modular, and maintainable code, along with comprehensive documentation and reports for model explainability, reproducibility, and auditability. Proactively monitor and maintain deployed models, ensuring reliability and performance in production environments with millions of concurrent users. Required Qualifications Bachelor’s or master’s degree in computer science, Machine Learning, Data Science, or a related technical field. 3 to 5 years of experience building and deploying AI/ML models in production environments with high-scale traffic and concurrency. Advanced proficiency in Python and modern AI/ML frameworks, including TensorFlow, PyTorch, Scikit-learn, and JAX. Hands-on expertise in at least two of the following domains: NLP, computer vision, time-series forecasting, or generative AI. Deep understanding of the end-to-end ML lifecycle, including data preprocessing, feature engineering, hyperparameter tuning, model evaluation, and deployment. Proven experience with cloud platforms (AWS, GCP, or Azure) and their AI/ML services (e.g., SageMaker, Vertex AI, or Azure ML). Strong knowledge of containerization (Docker, Kubernetes) and RESTful API development for secure and scalable model deployment. Familiarity with secure coding practices, data privacy regulations, and techniques for safeguarding AI systems against adversarial attacks. Preferred Skills Expertise in MLOps frameworks and tools such as MLflow, Kubeflow, or SageMaker for streamlined model lifecycle management. Hands-on experience with large language models (LLMs) or generative AI frameworks (e.g., Hugging Face Transformers, LangChain, or Llama). Proficiency in big data technologies and orchestration tools (e.g., Apache Spark, Airflow, or Kafka) for handling massive datasets and real-time pipelines. Experience with distributed training techniques (e.g., Horovod, Ray, or TensorFlow Distributed) for large-scale model development. Knowledge of CI/CD pipelines and infrastructure-as-code tools (e.g., Terraform, Ansible) for scalable and automated deployments. Familiarity with security frameworks and tools for AI systems, such as model hardening, differential privacy, or encrypted computation. Proven ability to work in global, client-facing roles, with strong communication skills to bridge technical and business teams. Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Role Description Job Title: Lead ML-Ops Engineer – GenAI & Scalable ML Systems Location: Any UST Job Type: Full-Time Experience Level: Senior / Lead Role Overview We are seeking a Lead ML-Ops Engineer to spearhead the end-to-end operationalization of machine learning and Generative AI models across our platforms. You will play a pivotal role in building robust, scalable ML pipelines, embedding responsible AI governance, and integrating innovative GenAI techniques—such as Retrieval-Augmented Generation (RAG) and LLM-based applications —into real-world systems. You will collaborate with cross-functional teams of data scientists, data engineers, product managers, and business stakeholders to ensure AI solutions are production-ready, resilient, and aligned with strategic business goals. A strong background in Dataiku or similar platforms is highly preferred. Key Responsibilities Model Development & Deployment Design, implement, and manage scalable ML pipelines using CI/CD practices. Operationalize ML and GenAI models, ensuring high availability, observability, and reliability. Automate data and model validation, versioning, and monitoring processes. Technical Leadership & Mentorship Act as a thought leader and mentor to junior engineers and data scientists on ML-Ops best practices. Define architecture standards and promote engineering excellence across ML-Ops workflows. Innovation & Generative AI Strategy Lead the integration of GenAI capabilities such as RAG and large language models (LLMs) into applications. Identify opportunities to drive business impact through cutting-edge AI technologies and frameworks. Governance & Compliance Implement governance frameworks for model explainability, bias detection, reproducibility, and auditability. Ensure compliance with data privacy, security, and regulatory standards in all ML/AI solutions. Must-Have Skills 5+ years of experience in ML-Ops, Data Engineering, or Machine Learning. Proficiency in Python, Docker, Kubernetes, and cloud services (AWS/GCP/Azure). Hands-on experience with CI/CD tools (e.g., GitHub Actions, Jenkins, MLflow, or Kubeflow). Deep knowledge of ML pipeline orchestration, model lifecycle management, and monitoring tools. Experience with LLM frameworks (e.g., LangChain, HuggingFace Transformers) and GenAI use cases like RAG. Strong understanding of responsible AI and MLOps governance best practices. Proven ability to work cross-functionally and lead technical discussions. Good-to-Have Skills Experience with Dataiku DSS or similar platforms (e.g., DataRobot, H2O.ai). Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) for GenAI retrieval tasks. Exposure to tools like Apache Airflow, Argo Workflows, or Prefect for orchestration. Understanding of ML evaluation metrics in a production context (drift detection, data integrity checks). Experience in mentoring, technical leadership, or project ownership roles. Why Join Us? Be at the forefront of AI innovation and shape how cutting-edge technologies drive business transformation. Join a collaborative, forward-thinking team with a strong emphasis on impact, ownership, and learning. Competitive compensation, remote flexibility, and opportunities for career advancement. Skills Artificial Intelligence,Python,ML-OPS Show more Show less

Experience : 5.00 + years Salary : INR 5000000.00 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Precanto) (*Note: This is a requirement for one of Uplers' client - A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams.) What do you need for this opportunity? Must have skills required: async workflows, MLOps, Ray Tune, Data Engineering, MLFlow, Supervised Learning, Time-Series Forecasting, Docker, machine_learning, NLP, Python, SQL A fast-growing, VC-backed B2B SaaS platform revolutionizing financial planning and analysis for modern finance teams. is Looking for: We are a fast-moving startup building AI-driven solutions to the financial planning workflow. We’re looking for a versatile Machine Learning Engineer to join our team and take ownership of building, deploying, and scaling intelligent systems that power our core product. Job Description- Full-time Team: Data & ML Engineering We’re looking for 5+ years of experience as a Machine Learning or Data Engineer (startup experience is a plus) What You Will Do- Build and optimize machine learning models — from regression to time-series forecasting Work with data pipelines and orchestrate training/inference jobs using Ray, Airflow, and Docker Train, tune, and evaluate models using tools like Ray Tune, MLflow, and scikit-learn Design and deploy LLM-powered features and workflows Collaborate closely with product managers to turn ideas into experiments and production-ready solutions Partner with Software and DevOps engineers to build robust ML pipelines and integrate them with the broader platform Basic Skills Proven ability to work creatively and analytically in a problem-solving environment Excellent communication (written and oral) and interpersonal skills Strong understanding of supervised learning and time-series modeling Experience deploying ML models and building automated training/inference pipelines Ability to work cross-functionally in a collaborative and fast-paced environment Comfortable wearing many hats and owning projects end-to-end Write clean, tested, and scalable Python and SQL code Leverage async workflows and cloud-native infrastructure (S3, Docker, etc.) for high-throughput data processing. Advanced Skills Familiarity with MLOps best practices Prior experience with LLM-based features or production-level NLP Experience with LLMs, vector stores, or prompt engineering Contributions to open-source ML or data tools TECH STACK Languages: Python, SQL Frameworks & Tools: scikit-learn, Prophet, pyts, MLflow, Ray, Ray Tune, Jupyter Infra: Docker, Airflow, S3, asyncio, Pydantic How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less