1036 Mlflow Jobs - Page 38

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including Experience, Skills And Additional Qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical Skills Requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting. Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements: Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Job Description Must Have Skills: Experience in design, build, and deployment of end-to-end AI solutions with a focus on LLMs and RAG (Retrieval-Augmented Generation) workflows. Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience with Oracle Fusion Cloud Applications (ERP and HCM) and their AI capabilities. Proficiency in developing AI chatbots using ODA (Oracle digital Assistance), Fusion APIs, OIC (Oracle integration cloud) and genAI services. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in programming languages (e.g., Java, Python) and databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference. Understanding of the security and compliance requirements for ML/GenAI implementations. /IC3 Career Level - IC3 Responsibilities Be a leader, a ‘doer’, with a vision & desire to contribute to a business with a technical project focus and mentality that centers around a superior customer experience. Bring entrepreneurial & innovative flair, with the tenacity to develop and prove delivery ideas independently, then share these as examples to improve the efficiency of the delivery of these solutions across EMEA. Working effectively across internal, external and culturally diverse lines of business to define and deliver customer success. Proactive approach to the task and self-learner. Self-motivated, you have the natural drive to learn and pick up new challenges. Results orientation, you won’t be satisfied until the job is done with the right quality! Ability to work in (virtual) teams. To get a specific job done often requires working together with many colleagues spread out in different countries. Comfortable in a collaborative, agile environment. Ability to adapt to change with a positive mindset. Good communication skills, both oral and written! You are able to not only understand complex technologies but also to explain to others in clear and simple terms. You can articulate key messages very clearly. Being able to present in front of customers. https://www.oracle.com/in/cloud/cloud-lift/ About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Job Description Must Have Skills: Experience in design, build, and deployment of end-to-end AI solutions with a focus on LLMs and RAG (Retrieval-Augmented Generation) workflows. Extensive knowledge of large language models, natural language processing techniques and prompt engineering. Experience with Oracle Fusion Cloud Applications (ERP and HCM) and their AI capabilities. Proficiency in developing AI chatbots using ODA (Oracle digital Assistance), Fusion APIs, OIC (Oracle integration cloud) and genAI services. Experience in testing and validation processes to ensure the models' accuracy and efficiency in real-world scenarios. Familiarity with Oracle Cloud Infrastructure or similar cloud platforms. Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. Analyzes problems, identifies solutions, and makes decisions. Demonstrates a willingness to learn, adapt, and grow professionally. Good to Have Skills: Experience in LLM architectures, model evaluation, and fine-tuning techniques. Hands-on experience with emerging LLM frameworks and plugins, such as LangChain, LlamaIndex, VectorStores and Retrievers, LLM Cache, LLMOps (MLFlow), LMQL, Guidance, etc. Proficiency in programming languages (e.g., Java, Python) and databases (e.g., Oracle, MySQL), developing and executing AI over any of the cloud data platforms, associated data stores, Graph Stores, Vector Stores and pipelines. Knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference. Understanding of the security and compliance requirements for ML/GenAI implementations. /IC3 Career Level - IC3 Responsibilities Be a leader, a ‘doer’, with a vision & desire to contribute to a business with a technical project focus and mentality that centers around a superior customer experience. Bring entrepreneurial & innovative flair, with the tenacity to develop and prove delivery ideas independently, then share these as examples to improve the efficiency of the delivery of these solutions across EMEA. Working effectively across internal, external and culturally diverse lines of business to define and deliver customer success. Proactive approach to the task and self-learner. Self-motivated, you have the natural drive to learn and pick up new challenges. Results orientation, you won’t be satisfied until the job is done with the right quality! Ability to work in (virtual) teams. To get a specific job done often requires working together with many colleagues spread out in different countries. Comfortable in a collaborative, agile environment. Ability to adapt to change with a positive mindset. Good communication skills, both oral and written! You are able to not only understand complex technologies but also to explain to others in clear and simple terms. You can articulate key messages very clearly. Being able to present in front of customers. https://www.oracle.com/in/cloud/cloud-lift/ About Us As a world leader in cloud solutions, Oracle uses tomorrow’s technology to tackle today’s challenges. We’ve partnered with industry-leaders in almost every sector—and continue to thrive after 40+ years of change by operating with integrity. We know that true innovation starts when everyone is empowered to contribute. That’s why we’re committed to growing an inclusive workforce that promotes opportunities for all. Oracle careers open the door to global opportunities where work-life balance flourishes. We offer competitive benefits based on parity and consistency and support our people with flexible medical, life insurance, and retirement options. We also encourage employees to give back to their communities through our volunteer programs. We’re committed to including people with disabilities at all stages of the employment process. If you require accessibility assistance or accommodation for a disability at any point, let us know by emailing accommodation-request_mb@oracle.com or by calling +1 888 404 2494 in the United States. Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. Show more Show less

Sub:TCS Virtual Drive – Databricks Architect Greetings from Tata Consultancy Services !!! TCS is hiring fo r Databricks Architect Experience : 10+ years Location: PAN India Job Role- Hands on Experience in ADF, Azure Databricks, Pyspark, Azure Data Factory, Unity Catalog, Data migrations, Data Security Good to have - Spark SQL, Spark Streaming, Kafka Hands on in Databricks on AWS, Apache Spark, AWS S3 (Data Lake), AWS Glue, AWS Redshift / Athena, AWS Data Catalog, Amazon Redshift, Amazon Athena, AWS RDS, AWS Glue, AWS EMR (Spark/Hadoop) CI/CD (CodePipeline, CodeBuild) Good to have - AWS Lambda, Python, AWS CI/CD, Kafka MLflow, TensorFlow, or PyTorch, Airflow, CloudWatch Show more Show less

Introduction: A Career at HARMAN Lifestyle We’re a global, multi-disciplinary team that’s putting the innovative power of technology to work and transforming tomorrow. As a member of HARMAN Lifestyle, you connect consumers with the power of superior sound. Contribute your talents to high-end, esteemed brands like JBL, Mark Levinson and Revel Unite your passion for audio innovation with high-tech product development Create pitch-perfect, cutting-edge technology that elevates the listening experience What You Will Do To perform in-depth analysis of data and machine learning models to identify insights and areas of improvement. Develop and implement models using both classical machine learning techniques and modern deep learning approaches. Deploy machine learning models into production, ensuring robust MLOps practices including CI/CD pipelines, model monitoring, and drift detection. Conduct fine-tuning and integrate Large Language Models (LLMs) to meet specific business or product requirements. Optimize models for performance and latency, including the implementation of caching strategies where appropriate. Collaborate cross-functionally with data scientists, engineers, and product teams to deliver end-to-end ML solutions. What You Need To Be Successful Utilized various statistical techniques to derive important insights and trends. Proven experience in machine learning model development and analysis using classical and neural networks based approaches. Strong understanding of LLM architecture, usage, and fine-tuning techniques. Solid understanding of statistics, data preprocessing, and feature engineering. Proficient in Python and popular ML libraries (scikit-learn, PyTorch, TensorFlow, etc.). Strong debugging and optimization skills for both training and inference pipelines. Familiarity with data formats and processing tools (Pandas, Spark, Dask). Experience working with transformer-based models (e.g., BERT, GPT) and Hugging Face ecosystem. Bonus Points if You Have Experience with MLOps tools (e.g., MLflow, Kubeflow, SageMaker, or similar). Experience with monitoring tools (Prometheus, Grafana, or custom solutions for ML metrics). Familiarity with cloud platforms (Sagemaker, AWS, GCP, Azure) and containerization (Docker, Kubernetes). Hands-on experience with MLOps practices and tools for deployment, monitoring, and drift detection. Exposure to distributed training and model parallelism techniques. Prior experience in AB testing ML models in production. What Makes You Eligible Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. 5-10 years relevant and Proven experience in developing and deploying generative AI models and agents in a professional setting. What We Offer Flexible work environment, allowing for full-time remote work globally for positions that can be performed outside a HARMAN or customer location Access to employee discounts on world-class Harman and Samsung products (JBL, HARMAN Kardon, AKG, etc.) Extensive training opportunities through our own HARMAN University Competitive wellness benefits Tuition reimbursement “Be Brilliant” employee recognition and rewards program An inclusive and diverse work environment that fosters and encourages professional and personal development You Belong Here HARMAN is committed to making every employee feel welcomed, valued, and empowered. No matter what role you play, we encourage you to share your ideas, voice your distinct perspective, and bring your whole self with you – all within a support-minded culture that celebrates what makes each of us unique. We also recognize that learning is a lifelong pursuit and want you to flourish. We proudly offer added opportunities for training, development, and continuing education, further empowering you to live the career you want. About HARMAN: Where Innovation Unleashes Next-Level Technology Ever since the 1920s, we’ve been amplifying the sense of sound. Today, that legacy endures, with integrated technology platforms that make the world smarter, safer, and more connected. Across automotive, lifestyle, and digital transformation solutions, we create innovative technologies that turn ordinary moments into extraordinary experiences. Our renowned automotive and lifestyle solutions can be found everywhere, from the music we play in our cars and homes to venues that feature today’s most sought-after performers, while our digital transformation solutions serve humanity by addressing the world’s ever-evolving needs and demands. Marketing our award-winning portfolio under 16 iconic brands, such as JBL, Mark Levinson, and Revel, we set ourselves apart by exceeding the highest engineering and design standards for our customers, our partners and each other. If you’re ready to innovate and do work that makes a lasting impact, join our talent community today! HARMAN is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or Protected Veterans status. HARMAN offers a great work environment, challenging career opportunities, professional training, and competitive compensation. (www.harman.com) Show more Show less

Job Description Alimentation Couche-Tard Inc., (ACT) is a global Fortune 200 company. A leader in the convenience store and fuel space with over 16,700 stores in 31 countries, serving more than 9 million customers each day. The India Data & Analytics Global Capability Centre is an integral part of ACT’s Global Data & Analytics Team and the Senior Data Scientist will be a key player on this team that will help grow analytics globally at ACT. The hired candidate will partner with multiple departments, including Global Marketing, Merchandising, Global Technology, and Business Units. About The Role The incumbent will be responsible for delivering advanced analytics projects that drive business results including interpreting business, selecting the appropriate methodology, data cleaning, exploratory data analysis, model building, and creation of polished deliverables. Responsibilities Analytics & Strategy Analyse large-scale structured and unstructured data; develop deep-dive analyses and machine learning models in retail, marketing, merchandising, and other areas of the business Utilize data mining, statistical and machine learning techniques to derive business value from store, product, operations, financial, and customer transactional data Apply multiple algorithms or architectures and recommend the best model with in-depth description to evangelize data-driven business decisions Utilize cloud setup to extract processed data for statistical modelling and big data analysis, and visualization tools to represent large sets of time series/cross-sectional data Operational Excellence Follow industry standards in coding solutions and follow programming life cycle to ensure standard practices across the project Structure hypothesis, build thoughtful analyses, develop underlying data models and bring clarity to previously undefined problems Partner with Data Engineering to build, design and maintain core data infrastructure, pipelines and data workflows to automate dashboards and analyses Stakeholder Engagement Working collaboratively across multiple sets of stakeholders – Business functions, Data Engineers, Data Visualization experts to deliver on project deliverables Articulate complex data science models to business teams and present the insights in easily understandable and innovative formats Job Requirements Education Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.) Relevant Experience 5–7 years of relevant working experience in a data science/advanced analytics role Behavioural Skills Delivery Excellence Business disposition Social intelligence Innovation and agility Knowledge Functional Analytics (Supply chain analytics, Marketing Analytics, Customer Analytics) Statistical modelling using Analytical tools (R, Python, KNIME, etc.) and use big data technologies Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Practical experience building scalable ML models, feature engineering, model evaluation metrics, and statistical inference. Practical experience deploying models using MLOps tools and practices (e.g., MLflow, DVC, Docker, etc.) Strong coding proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Big data technologies & framework (AWS, Azure, GCP, Hadoop, Spark, etc.) Enterprise reporting systems, relational (MySQL, Microsoft SQL Server etc.), non-relational (MongoDB, DynamoDB) database management systems and Data Engineering tools Business intelligence & reporting (Power BI, Tableau, Alteryx, etc.) Microsoft Office applications (MS Excel, etc.) Show more Show less

Senior Data Engineer with ML About the Role We are seeking an experienced Senior Data Engineer with 5-10 years of experience to join our data team. In this role, you will design, build, and maintain robust data pipelines that support both training and inference for our machine learning systems. You will work closely with data scientists to ensure seamless integration between data infrastructure and ML models. Key Responsibilities - Design, develop, and maintain scalable data pipelines for ML training and inference - Collaborate with data scientists to optimize data flows for model training and deployment - Implement and maintain ETL processes to transform raw data into formats suitable for analysis - Ensure data quality, reliability, and accessibility across the organization - Build and optimize data infrastructure to support ML operations - Troubleshoot and resolve data pipeline issues in production environments Required Qualifications - Bachelor's degree in Computer Science, Engineering, or related technical field - 5-10 years of professional experience in data engineering - Strong programming skills in Python or scala. - Extensive experience with data processing frameworks (Apache Spark) - Proficiency in SQL - Experience building and maintaining ML training and inference pipelines - Experience with AWS data services - Experience with version control systems and CI/CD practices Preferred Skills - Experience with MLOps tools and practices (MLflow, Kubeflow, etc.) - Expeirence with Databricks - Familiarity with feature stores and feature engineering best practices - Understanding of distributed computing principles and optimization techniques - Experience with data modeling and data warehouse design Personal Attributes - Strong problem-solving skills with attention to detail - Excellent communication skills to collaborate with technical and non-technical stakeholders - Self-motivated with the ability to work independently and lead projects - Adaptable to changing requirements and technologies - Passion for building reliable, scalable data systems Show more Show less

Senior Technical Architect Machine Learning Solutions We are looking for a Senior Technical Architect with deep expertise in Machine Learning (ML), Artificial Intelligence (AI) , and scalable ML system design . This role will focus on leading the end-to-end architecture of advanced ML-driven platforms, delivering impactful, production-grade AI solutions across the enterprise. Key Responsibilities Lead the architecture and design of enterprise-grade ML platforms , including data pipelines, model training pipelines, model inference services, and monitoring frameworks. Architect and optimize ML lifecycle management systems (MLOps) to support scalable, reproducible, and secure deployment of ML models in production. Design and implement retrieval-augmented generation (RAG) systems, vector databases , semantic search , and LLM orchestration frameworks (e.g., LangChain, Autogen). Define and enforce best practices in model development, versioning, CI/CD pipelines , model drift detection, retraining, and rollback mechanisms. Build robust pipelines for data ingestion, preprocessing, feature engineering , and model training at scale , using batch and real-time streaming architectures. Architect multi-modal ML solutions involving NLP, computer vision, time-series, or structured data use cases. Collaborate with data scientists, ML engineers, DevOps, and product teams to convert research prototypes into scalable production services . Implement observability for ML models including custom metrics, performance monitoring, and explainability (XAI) tooling. Evaluate and integrate third-party LLMs (e.g., OpenAI, Claude, Cohere) or open-source models (e.g., LLaMA, Mistral) as part of intelligent application design. Create architectural blueprints and reference implementations for LLM APIs, model hosting, fine-tuning, and embedding pipelines . Guide the selection of compute frameworks (GPUs, TPUs), model serving frameworks (e.g., TorchServe, Triton, BentoML) , and scalable inference strategies (batch, real-time, streaming). Drive AI governance and responsible AI practices including auditability, compliance, bias mitigation, and data protection. Stay up to date on the latest developments in ML frameworks, foundation models, model compression, distillation, and efficient inference . 14. Ability to coach and lead technical teams , fostering growth, knowledge sharing, and technical excellence in AI/ML domains. Experience managing the technical roadmap for AI-powered products , documentations ensuring timely delivery, performance optimization, and stakeholder alignment. Required Qualifications Bachelors or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 8+ years of experience in software architecture , with 5+ years focused specifically on machine learning systems and 2 years in leading team. Proven expertise in designing and deploying ML systems at scale , across cloud and hybrid environments. Strong hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn). Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Qdrant) and embedding models (e.g., SBERT, OpenAI, Cohere). Demonstrated proficiency in MLOps tools and platforms : MLflow, Kubeflow, SageMaker, Vertex AI, DataBricks, Airflow, etc. In-depth knowledge of cloud AI/ML services on AWS, Azure, or GCP – including certification(s) in one or more platforms. Experience with containerization and orchestration (Docker, Kubernetes) for model packaging and deployment. Ability to design LLM-based systems , including hybrid models (open-source + proprietary), fine-tuning strategies, and prompt engineering. Solid understanding of security, compliance , and AI risk management in ML deployments. Preferred Skills Experience with AutoML , hyperparameter tuning, model selection, and experiment tracking. Knowledge of LLM tuning techniques : LoRA, PEFT, quantization, distillation, and RLHF. Knowledge of privacy-preserving ML techniques , federated learning, and homomorphic encryption Familiarity with zero-shot, few-shot learning , and retrieval-enhanced inference pipelines. Contributions to open-source ML tools or libraries. Experience deploying AI copilots, agents, or assistants using orchestration frameworks.

CSQ326R35 Mission The Machine Learning (ML) Practice team is a highly specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help our customers build, scale, and optimize ML pipelines, as well as put those pipelines into production. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in LLMs, MLOps, and ML more broadly. This role can be remote based in India. The Impact You Will Have Develop LLM solutions on customer data such as RAG architectures on enterprise knowledge repos, querying structured data with natural language, and content generation Build, scale, and optimize customer data science workloads and apply best in class MLOps to productionize these workloads across a variety of domains Advise data teams on various data science such as architecture, tooling, and best practices Present at conferences such as Data+AI Summit Provide technical mentorship to the larger ML SME community in Databricks Collaborate cross-functionally with the product and engineering teams to define priorities and influence the product roadmap What we look for: Experience building Generative AI applications, including RAG, agents, text2sql, fine-tuning, and deploying LLMs, with tools such as HuggingFace, Langchain, and OpenAI 5+ years of hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch Experience building production-grade machine learning deployments on AWS, Azure, or GCP Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike Passion for collaboration, life-long learning, and driving business value through ML [Preferred] Experience working with Databricks & Apache Spark to process large-scale distributed datasets 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

Description RESPONSIBILITIES Design and implement CI/CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails). Provision and manage AI infrastructure across cloud hyperscalers (AWS/GCP), using infrastructure-as-code tools -strong preference for Terraform-. Maintain containerized environments (Docker, Kubernetes) optimized for GPU workloads and distributed compute. Support vector database, feature store, and embedding store deployments (e.g., pgVector, Pinecone, Redis, Featureform. MongoDB Atlas, etc). Monitor and optimize performance, availability, and cost of AI workloads, using observability tools (e.g., Prometheus, Grafana, Datadog, or managed cloud offerings). Collaborate with data scientists, AI/ML engineers, and other members of the platform team to ensure smooth transitions from experimentation to production. Implement security best practices including secrets management, model access control, data encryption, and audit logging for AI pipelines. Help support the deployment and orchestration of agentic AI systems (LangChain, LangGraph, CrewAI, Copilot Studio, AgentSpace, etc.). Must Haves: 4+ years of DevOps or infrastructure engineering experience. Preferably with 2+ years in AI/ML environments. Hands-on experience with cloud-native services (AWS Bedrock/SageMaker, GCP Vertex AI, or Azure ML) and GPU infrastructure management. Strong skills in CI/CD tools (GitHub Actions, ArgoCD, Jenkins) and configuration management (Ansible, Helm, etc.). Proficient in scripting languages like Python, Bash, -Go or similar is a nice plus-. Experience with monitoring, logging, and alerting systems for AI/ML workloads. Deep understanding of Kubernetes and container lifecycle management. Bonus Attributes: Exposure to MLOps tooling such as MLflow, Kubeflow, SageMaker Pipelines, or Vertex Pipelines. Familiarity with prompt engineering, model fine-tuning, and inference serving. Experience with secure AI deployment and compliance frameworks Knowledge of model versioning, drift detection, and scalable rollback strategies. Abilities: Ability to work with a high level of initiative, accuracy, and attention to detail. Ability to prioritize multiple assignments effectively. Ability to meet established deadlines. Ability to successfully, efficiently, and professionally interact with staff and customers. Excellent organization skills. Critical thinking ability ranging from moderately to highly complex. Flexibility in meeting the business needs of the customer and the company. Ability to work creatively and independently with latitude and minimal supervision. Ability to utilize experience and judgment in accomplishing assigned goals. Experience in navigating organizational structure. Show more Show less

P-926 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. And we're only getting started in Bengaluru , India ! As a software engineer with a backend focus, you will work with your team to build infrastructure for the Databricks platform at scale. The Impact You'll Have Our backend teams cover a diverse range of domains, from core compute fabric resource management to service platforms and infrastructure. For example, you might work on challenges such as: Supporting Databricks' growth by building foundational infrastructure platforms that enable seamless operation across numerous geographic regions and cloud providers. Implementing cloud-agnostic infrastructure abstractions to help Databricks engineers more efficiently manage and operate their services. Develop tools and processes that drive engineering efficiency at Databricks. We enhance the developer experience for Databricks engineers across various areas, including programming languages, linters, static analysis, IDEs, remote development environments, automated release pipelines, and test automation frameworks. Our current focus is on optimizing the Rust development experience across the organization. What We Look For BS (or higher) in Computer Science, or a related field 6+ 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 Proficiency in one or more backend languages such as Java, Scala, or Go. Hands-on experience in developing and operating backend systems. Ability to contribute effectively throughout all project phases, from initial design and development to implementation and ongoing operations, with guidance from senior team members. 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

We are seeking a skilled Lead Software Engineer to join our team and lead a project focused on developing GenAI applications using Large Language Models (LLMs) and Python programming . In this role, you will be responsible for designing and optimizing Al-generated text prompts to maximize effectiveness for various applications. You will also collaborate with cross-functional teams to ensure seamless integration of optimized prompts into the overall product or system. Your expertise in prompt engineering principles and techniques will allow you to guide models to desired outcomes and evaluate prompt performance to identify areas for optimization and iteration. Responsibilities Design, develop, test and refine AI-generated text prompts to maximize effectiveness for various applications Ensure seamless integration of optimized prompts into the overall product or system Rigorously evaluate prompt performance using metrics and user feedback Collaborate with cross-functional teams to understand requirements and ensure prompts align with business goals and user needs Document prompt engineering processes and outcomes, educate teams on prompt best practices and keep updated on the latest AI advancements to bring innovative solutions to the project Requirements 7 to 12 years of relevant professional experience Expertise in Python programming including experience with Al/machine learning frameworks like TensorFlow, PyTorch, Keras, Langchain, MLflow, Promtflow 2-5 years of working knowledge of NLP and LLMs like BERT, GPT-3/4, T5, etc. Knowledge of how these models work and how to fine-tune them Expertise in prompt engineering principles and techniques like chain of thought, in-context learning, tree of thought, etc. Knowledge of retrieval augmented generation (RAG) Strong analytical and problem-solving skills with the ability to think critically and troubleshoot issues Excellent communication skills, both verbal and written in English at a B2+ level for collaborating across teams, explaining technical concepts, and documenting work outcomes Show more Show less

NeuraTalk, an AI company backed by Singapore investors, is seeking a Python MLOps Engineer to join our founding team. Opportunity For Experienced candidates only. This role starts as a 3-month provisional period with a fixed pay of ₹25,000 per month. Upon successful completion, candidates will be offered a full-time role with a package of ₹6 LPA. - Annual Bonus Extra Role Overview Design, build, and maintain advanced ML Ops pipelines for cutting-edge AI models, focusing on agentic RAG, LangChain integration, fine-tuning, and scalable deployment. Open for experienced candidates passionate about ML infrastructure and automation. Technical Requirements Strong Python programming skills (Required) Experience with advanced Retrieval-Augmented Generation (RAG) systems and agentic AI design Proficiency with LangChain framework for building LLM applications Experience in fine-tuning large language models on domain-specific data Skilled in building end-to-end ML pipelines for training, validation, and deployment Familiarity with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure) Experience with CI/CD for ML models and monitoring model performance post-deployment Understanding of vector databases and embedding techniques (e.g., FAISS, Pinecone) Knowledge of model serving frameworks (e.g., FastAPI, TorchServe) Experience with experiment tracking and hyperparameter tuning tools (e.g., MLflow, Weights & Biases) Basic understanding of NLP and transformer architectures Responsibilities Develop and maintain scalable MLOps pipelines for advanced AI solutions Build and optimize agentic RAG workflows integrating LangChain and other LLM tools Fine-tune models on specialized datasets to improve accuracy and relevance Automate model deployment and monitoring to ensure high availability and performance Collaborate closely with data scientists and ML researchers to operationalize models Implement logging, alerting, and performance tracking for production models Contribute to infrastructure design for seamless model updates and rollback For Experienced Developers 2+ years in Python-based MLOps or ML Engineering roles Hands-on experience with LangChain or similar agentic AI frameworks Strong cloud deployment and container orchestration skills Proven track record of delivering production ML pipelines Ability to work independently and as part of a cross-functional team Benefits Remote work flexibility Early-stage equity (ESOP) Direct collaboration with the founding AI research and product team Opportunities for growth and leadership in AI infrastructure Future Singapore relocation opportunity Continuous learning and innovation-driven environment Work Culture Innovation-driven AI startup Remote-first with flexible working hours Transparent communication and team-oriented Direct impact on cutting-edge AI product development Equal opportunity employer promoting diversity and inclusion #AI #MLOps #Python #LangChain #RAG #MLDeployment #RemoteWork #Startup #India #Singapore Show more Show less

FairAds AI is at the forefront of revolutionizing advertising. We're seeking a highly motivated Machine Learning Engineer / Deep Learning Engineer Intern to join our pioneering team for an immediate start in Mumbai, Maharashtra, India. This is a paid, in-person position . You'll dive deep into developing and deploying, DPDP-compliant ML/DL models for real-time analytics. This is a unique opportunity to work on impactful projects involving Computer Vision, real-time data processing, and privacy-preserving AI. What You'll Help Build & Responsibilities * Develop & Implement ML/DL Models: Design, train, and fine-tune models like YOLO, DeepSORT, and DeepFace for tasks such as impression counting, dwell time analysis, and anonymized demographic analysis. * Advanced Computer Vision Tasks: Apply your OpenCV and CV knowledge for object detection, tracking, pose estimation, and image segmentation on real-world video streams. * Data Preprocessing & Management: Handle raw camera data, including cleaning, annotation, and implementing anonymization techniques (e.g., blurring, feature embeddings) to ensure DPDP Act compliance. Manage datasets using tools like DVC or cloud storage. * Edge Computing & Deployment: Optimize and deploy models on edge devices (e.g., NVIDIA Jetson, Raspberry Pi), managing real-time processing pipelines and considering power/thermal constraints. * Real-Time Analytics: Design streaming data pipelines for video feeds and optimize inference speed (e.g., using TensorRT) to deliver low-latency KPIs. * Privacy by Design: Actively contribute to building privacy-preserving ML pipelines, understanding DPDP Act principles (data minimization, consent, purpose limitation) and implementing secure data handling. * Containerization & CI/CD: Utilize Docker to package and deploy models consistently. Contribute to CI/CD pipelines for automated testing and deployment. Core Technical Skills We're Looking For * Python Programming: Proficiency in Python for ML/DL development, including libraries like PyTorch, TensorFlow, OpenCV, NumPy, Pandas, and Matplotlib. Ability to write modular, reusable code. * Machine Learning & Deep Learning: Strong understanding of supervised/unsupervised learning, neural networks (CNNs), architectures (YOLO, ResNet, ViT), transfer learning, loss functions, optimizers, and regularization. * Computer Vision: Expertise with OpenCV for image/video processing, object detection, tracking, and pose estimation. Experience handling real-time video streams. * Data Preprocessing: Skills in data cleaning, transformation, annotation, and implementing anonymization techniques. Key Domain-Specific & Deployment Skills Needed * Edge Computing: Experience or strong interest in optimizing models (pruning, quantization) for resource-constrained edge hardware (NVIDIA Jetson, Raspberry Pi) and managing real-time edge processing. * Real-Time Analytics: Ability to design streaming data pipelines and optimize for low-latency inference. * Docker & Containerization: Writing Dockerfiles and managing containers for ML model deployment. * Edge Device Deployment: Configuring edge hardware (CUDA, cuDNN), managing cross-compilation, monitoring, and potentially OTA updates. * Version Control & CI/CD (Git, GitHub Actions/Jenkins): Experience with versioning code and models (MLflow, DVC) and automation. * Cloud Integration (Optional but valued): Familiarity with AWS, Azure, or GCP for aggregating anonymized KPIs or model training. API development (Flask/FastAPI) is a plus. Soft Skills for Success * Problem-Solving & Analytical Thinking: Ability to tackle complex challenges in model performance. * Attention to Detail: Meticulous approach to data handling, model accuracy, and compliance requirements. * Pro Vibe Coder: You're someone who can skillfully navigate and debug code, especially code that might have been initially generated or assisted by AI, ensuring its robustness and efficiency. What We Offer * Pioneering Projects: Work on groundbreaking analytics solutions using advanced AI and edge computing. * Hands-on Experience: Gain invaluable experience with the full lifecycle of ML models – from conception to deployment on edge devices. * Mentorship: Learn from experienced professionals in AI, Computer Vision, and privacy-preserving technologies. * Impactful Contribution: Directly contribute to building a more intelligent and compliant ecosystem. Show more Show less

We're Hiring! Machine Learning Engineer for a B2B SaaS based startup in Noida. 🔹 Position: Machine Learning Engineer 🔹 Experience: 3.5 Years to 5 Years 🔹 Location: Noida, Sector 90 🔹 Work Mode: 5 Days | Work From Office 🔹 Notice Period: Immediate to 30 Days Key Responsibilities Design, develop, and optimize machine learning models for various business applications. Build and maintain scalable AI feature pipelines for efficient data processing and model training. Develop robust data ingestion, transformation, and storage solutions for big data. Implement and optimize ML workflows, ensuring scalability and efficiency. Monitor and maintain deployed models, ensuring performance, reliability, and retraining when necessary. Qualifications and Experience Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 3.5+ years of experience in machine learning, deep learning, or data science roles. Proficiency in Python and ML frameworks/tools such as PyTorch, Langchain Experience with data processing frameworks like Spark, Dask, Airflow, and Dagster Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Experience with MLOps tools like MLflow, Kubeflow Familiarity with containerisation and orchestration tools like Docker and Kubernetes. Excellent problem-solving skills and ability to work in a fast-paced environment. Strong communication and collaboration skills. If you’re ready to take on a leadership role and thrive in a dynamic startup environment, share your profile at gautam@mounttalent.com. Show more Show less

About Hakkoda Hakkoda, an IBM Company, is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone’s input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, India and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role Description Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic researchand industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Qualifications Education: PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Benefits Health Insurance Paid leave Technical training and certifications Robust learning and development opportunities Incentive Toastmasters Food Program Fitness Program Referral Bonus Program Hakkoda is committed to fostering diversity, equity, and inclusion within our teams. A diverse workforce enhances our ability to serve clients and enriches our culture. We encourage candidates of all races, genders, sexual orientations, abilities, and experiences to apply, creating a workplace where everyone can succeed and thrive. Ready to take your career to the next level? 🚀 💻 Apply today👇 and join a team that’s shaping the future!! Hakkoda is an IBM subsidiary which has been acquired by IBM and will be integrated in the IBM organization. Hakkoda will be the hiring entity. By Proceeding with this application, you understand that Hakkoda will share your personal information with other IBM subsidiaries involved in your recruitment process, wherever these are located. More information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here. Show more Show less

Candidates for this position are preferred to be based in Bangalore, India and will be expected to comply with their team's hybrid work schedule requirements. Who We Are Wayfair’s Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for an experienced Machine Learning Scientist II to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair’s revenue. What you’ll do Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support recommendations for Ads campaigns and other optimizations. Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience. Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped machine learning solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems. Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. We Are a Match Because You Have: Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, or related field. 6-9 years of industry experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale. Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Familiarity with machine learning model development frameworks, machine learning orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity Nice to have Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks). Experience in computational advertising, bidding algorithms, or search ranking Experience with deep learning frameworks like PyTorch, Tensorflow, etc. Show more Show less

Who we are Wayfair’s Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for Machine Learning Scientists to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair’s revenue. What you’ll do Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. What you’ll need 3+ years of industry experience with a Bachelor/ Master’s degree or minimum of 1-2 years of industry experience with PhD in Computer Science, Mathematics, Statistics, or related field. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Strong written and verbal communication skills Intellectual curiosity and enthusiastic about continuous learning Nice to have Experience with Python machine learning ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML) Familiarity with GCP (or AWS, Azure), machine learning model development frameworks, machine learning orchestration tools (Airflow, Kubeflow or MLFlow) Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc. Experience with deep learning frameworks like PyTorch, Tensorflow, etc. Show more Show less

Job Summary In this role, you will lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI. Job Description Company Overview: Outsourced is a leading ISO certified India & Philippines offshore outsourcing company that provides dedicated remote staff to some of the world's leading international companies. Outsourced is recognized as one of the Best Places to Work and has achieved Great Place to Work Certification. We are committed to providing a positive and supportive work environment where all staff can thrive. As an Outsourced staff member, you will enjoy a fun and friendly working environment, competitive salaries, opportunities for growth and development, work-life balance, and the chance to share your passion with a team of over 1000 talented professionals. Job Responsibilities Lead the architecture and implementation of MLOps/LLMOps systems within OpenShift AI, establishing best practices for scalability, reliability, and maintainability while actively contributing to relevant open source communities Design and develop robust, production-grade features focused on AI trustworthiness, including model monitoring Drive technical decision-making around system architecture, technology selection, and implementation strategies for key MLOps components, with a focus on open source technologies Define and implement technical standards for model deployment, monitoring, and validation pipelines, while mentoring team members on MLOps best practices and engineering excellence Collaborate with product management to translate customer requirements into technical specifications, architect solutions that address scalability and performance challenges, and provide technical leadership in customer-facing discussions Lead code reviews, architectural reviews, and technical documentation efforts to ensure high code quality and maintainable systems across distributed engineering teams Identify and resolve complex technical challenges in production environments, particularly around model serving, scaling, and reliability in enterprise Kubernetes deployments Partner with cross-functional teams to establish technical roadmaps, evaluate build-vs-buy decisions, and ensure alignment between engineering capabilities and product vision Provide technical mentorship to team members, including code review feedback, architecture guidance, and career development support while fostering a culture of engineering excellence Required Qualifications 5+ years of software engineering experience, with at least 4 years focusing on ML/AI systems in production environments Strong expertise in Python, with demonstrated experience building and deploying production ML systems Deep understanding of Kubernetes and container orchestration, particularly in ML workload contexts Extensive experience with MLOps tools and frameworks (e.g., KServe, Kubeflow, MLflow, or similar) Track record of technical leadership in open source projects, including significant contributions and community engagement Proven experience architecting and implementing large-scale distributed systems Strong background in software engineering best practices, including CI/CD, testing, and monitoring Experience mentoring engineers and driving technical decisions in a team environment Preferred Qualifications Experience with Red Hat OpenShift or similar enterprise Kubernetes platforms Contributions to ML/AI open source projects, particularly in the MLOps/GitOps space Background in implementing ML model monitoring Experience with LLM operations and deployment at scale Public speaking experience at technical conferences Advanced degree in Computer Science, Machine Learning, or related field Experience working with distributed engineering teams across multiple time zones What we Offer Health Insurance: We provide medical coverage up to 20 lakh per annum, which covers you, your spouse, and a set of parents. This is available after one month of successful engagement. Professional Development: You'll have access to a monthly upskill allowance of ₹5000 for continued education and certifications to support your career growth. Leave Policy: Vacation Leave (VL): 10 days per year, available after probation. You can carry over or encash up to 5 unused days. Casual Leave (CL): 8 days per year for personal needs or emergencies, available from day one. Sick Leave: 12 days per year, available after probation. Flexible Work Hours or Remote Work Opportunities – Depending on the role and project. Outsourced Benefits such as Paternity Leave, Maternity Leave, etc. Show more Show less

Company Description Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com Job Description Blend is hiring a Senior Data Scientist (Generative AI) to spearhead the development of advanced AI-powered classification and matching systems on Databricks. You will contribute to flagship programs like the Diageo AI POC by building RAG pipelines, deploying agentic AI workflows, and scaling LLM-based solutions for high-precision entity matching and MDM modernization. Key Responsibilities Design and implement end-to-end AI pipelines for product classification, fuzzy matching, and deduplication using LLMs, RAG, and Databricks-native workflows. Develop scalable, reproducible AI solutions within Databricks notebooks and job clusters, leveraging Delta Lake, MLflow, and Unity Catalog. Engineer Retrieval-Augmented Generation (RAG) workflows using vector search and integrate with Python-based matching logic. Build agent-based automation pipelines (rule-driven + GenAI agents) for anomaly detection, compliance validation, and harmonization logic. Implement explainability, audit trails, and governance-first AI workflows aligned with enterprise-grade MDM needs. Collaborate with data engineers, BI teams, and product owners to integrate GenAI outputs into downstream systems. Contribute to modular system design and documentation for long-term scalability and maintainability. Qualifications Bachelor’s/Master’s in Computer Science, Artificial Intelligence, or related field. 5+ years of overall Data Science experience with 2+ years in Generative AI / LLM-based applications. Deep experience with Databricks ecosystem: Delta Lake, MLflow, DBFS, Databricks Jobs & Workflows. Strong Python and PySpark skills with ability to build scalable data pipelines and AI workflows in Databricks. Experience with LLMs (e.g., OpenAI, LLaMA, Mistral) and frameworks like LangChain or LlamaIndex. Working knowledge of vector databases (e.g., FAISS, Chroma) and prompt engineering for classification/retrieval. Exposure to MDM platforms (e.g., Stibo STEP) and familiarity with data harmonization challenges. Experience with explainability frameworks (e.g., SHAP, LIME) and AI audit tooling. Preferred Skills Knowledge of agentic AI architectures and multi-agent orchestration. Familiarity with Azure Data Hub and enterprise data ingestion frameworks. Understanding of data governance, lineage, and regulatory compliance in AI systems. Additional Information Thrive & Grow with Us : Competitive Salary: Your skills and contributions are highly valued here, and we make sure your salary reflects that, rewarding you fairly for the knowledge and experience you bring to the table. Dynamic Career Growth: Our vibrant environment offers you the opportunity to grow rapidly, providing the right tools, mentorship, and experiences to fast-track your career. Idea Tanks: Innovation lives here. Our "Idea Tanks" are your playground to pitch, experiment, and collaborate on ideas that can shape the future. Growth Chats: Dive into our casual "Growth Chats" where you can learn from the best—whether it's over lunch or during a laid-back session with peers, it's the perfect space to grow your skills. Snack Zone: Stay fuelled and inspired! In our Snack Zone, you'll find a variety of snacks to keep your energy high and ideas flowing. Recognition & Rewards: We believe great work deserves to be recognized. Expect regular Hive-Fives, shoutouts and the chance to see your ideas come to life as part of our reward program. Fuel Your Growth Journey with Certifications: We’re all about your growth groove! Level up your skills with our support as we cover the cost of your certifications. Show more Show less

Job Description: Position: Senior Technical Specialist – Data Science Location: Chennai Experience: 8+ Years Domain Expertise: AI/ML, Data Science, Cloud, DevOps, and MLOps Education: B.E. (ECE), MBA (Big Data Analytics). Job Summary: We are seeking an experienced Senior Technical Specialist - Data Science to lead AI/ML initiatives, design scalable data-driven solutions, and drive innovation. The ideal candidate will have strong expertise in AI/ML, data engineering, cloud technologies (Azure), and MLOps, with experience in managing teams and delivering AI-powered solutions for business challenges. Key Responsibilities: • Lead and mentor a team of Data Scientists to develop and deploy AI/ML models. • Architect end-to-end Machine Learning & AI solutions for complex business problems. • Design and implement Generative AI applications, including RAG-based chatbots using LLMs, LangChain, and Azure OpenAI. • Build, deploy, and monitor MLOps pipelines using MLFlow, Kubeflow, and Azure MLOps. • Develop predictive modeling, NLP applications, and deep learning frameworks using TensorFlow, PyTorch, and BERT. • Conduct data analysis and visualization using Power BI, Tableau, Matplotlib, and Streamlit. • Work with DevOps teams to automate ML workflows, optimize cloud infrastructure, and enhance model scalability. • Collaborate with business teams to define AI strategy, data-driven insights, and process improvements. • Research and implement the latest advancements in AI/ML to improve model accuracy and efficiency. Required Skills & Expertise: • Programming: Python, PowerShell, Bash, Perl • Machine Learning & Deep Learning: SVM, KNN, XGBoost, TensorFlow, PyTorch, LSTM • NLP & Generative AI: Spacy, BERT, LangChain, LlamaIndex, LLOps • Data Visualization: Tableau, Power BI, Matplotlib, Streamlit • Cloud & MLOps: Azure ML Studio, Azure OpenAI, Docker, Jenkins, GitHub, MLFlow, ClearML • Database & Big Data: MS-SQL, Data Preprocessing, Feature Engineering Preferred Qualifications: • Azure Data Scientist Certification • HackerRank Python & SQL Certification • Udacity NLP & Deep Learning Certifications Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

Overview We are PepsiCo PepsiCo is one of the world's leading food and beverage companies with more than $79 Billion in Net Revenue and a global portfolio of diverse and beloved brands. We have a complementary food and beverage portfolio that includes 22 brands that each generate more than $1 Billion in annual retail sales. PepsiCo's products are sold in more than 200 countries and territories around the world. PepsiCo's strength is its people. We are over 250,000 game changers, mountain movers and history makers, located around the world, and united by a shared set of values and goals. We believe that acting ethically and responsibly is not only the right thing to do, but also the right thing to do for our business. At PepsiCo, we aim to deliver top-tier financial performance over the long term by integrating sustainability into our business strategy, leaving a positive imprint on society and the environment. We call this Winning with Pep+ Positive . For more information on PepsiCo and the opportunities it holds, visit www.pepsico.com. PepsiCo Data Analytics & AI Overview: With data deeply embedded in our DNA, PepsiCo Data, Analytics and AI (DA&AI) transforms data into consumer delight. We build and organize business-ready data that allows PepsiCo’s leaders to solve their problems with the highest degree of confidence. Our platform of data products and services ensures data is activated at scale. This enables new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise. The Data Science Pillar in DA&AI will be the organization where Data Scientist and ML Engineers report to in the broader D+A Organization. Also DS will lead, facilitate and collaborate on the larger DS community in PepsiCo. DS will provide the talent for the development and support of DS component and its life cycle within DA&AI Products. And will support “pre-engagement” activities as requested and validated by the prioritization framework of DA&AI. Data Scientist-Gurugram and Hyderabad The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Machine Learning Services and Pipelines. Responsibilities Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure/AWS/GCP Pipelines. Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications Minimum 3years of hands-on work experience in data science / Machine learning Minimum 3year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers. BE/BS in Computer Science, Math, Physics, or other technical fields. Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models Programming Skills - Hands-on experience in statistical programming languages like Python and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Any Cloud - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience in Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills Show more Show less

This role is for one of Weekday's clients Salary range: Rs 4000000 - Rs 6500000 (ie INR 40-65 LPA) Min Experience: 10 years JobType: full-time About the role As a machine learning operations leader, together with Data Science and Engineering teams, you will lead a team that creates and maintains impactful solutions for our brands across the world. From traditional machine learning to large language models, you will work and lead throughout the model lifecycle. Responsibilities: Leadership: MLOps is a team sport, and we require a leader who can elevate everyone in the MLOps organization. While technical skills and vision are required, your leadership skills will take AI and machine learning from theoretical to operational, delivering tangible value to both customers and internal teams. Pipeline Management: Architect, implement, and maintain scalable ML pipelines, with seamless integration from data ingestion to production deployment. Model Monitoring: Lead the operationalization of machine learning models, ensuring hundreds of models are continuously monitored, retrained, and optimized in real-time environments Deployment: Deploy machine learning solutions in the cloud, securely and cost effectively. Reporting: Effectively communicate actionable insights across teams using both automatic (e.g., alerts) and non-automatic methods. The type of game changing candidate we are looking for: Seasoned: Demonstrated experience of 10-15 years successfully leading teams both formally and informally. Transparent: Willingness to identify and admit errors and seek out opportunities to continually improve both in their own work and across the team. Communication: MLOps is a central node in a complex system. Clear, actionable, and concise communication, both written and verbal is a must. Coaching and Team Advancement: An MLOps leader is continually developing team members and fostering a constant flow of communication and improvement across team members. Master's/PhD degree or a strong demonstration of technical expertise in Computer Science, Machine Learning, Data Science, or a related field Multiple years of direct extensive experience with AWS Multiple years of experience with MLOps monitoring and testing tools Ability to prioritize projects effectively once clear vision and goals are identified Excited to empower DS with tools, practices, and training that simplify MLOps enough for Data Science to increasingly practice MLOps on their own and own products in production.