1036 Mlflow Jobs - Page 31

Kalina , Mumbai, Maharashtra, India Department DIGITAL Job posted on Jun 02, 2025 Employee Type Permanent Experience range (Years) 4 years - 9 years Key Responsibilities: Lead the design, development, and deployment of predictive models, optimization algorithms, and statistical analyses. Translate complex business problems into data science solutions using machine learning, deep learning, NLP, and statistical modeling. Collaborate with product managers, engineers, and business stakeholders to understand objectives and deliver actionable insights. Mentor junior data scientists and analysts, and drive best practices in experimentation, coding standards, and model governance. Conduct exploratory data analysis, feature engineering, and model validation to ensure accuracy and robustness. Present findings and recommendations clearly to both technical and non-technical stakeholders. Stay up to date with the latest trends in AI/ML, and recommend new tools or techniques as appropriate. Contribute to the development of data science pipelines and MLOps practices for scalable and reproducible model deployment. Qualifications: Master’s or PhD in Computer Science, Statistics, Mathematics, Data Science, or related field. 8+ years of experience in data science, analytics, or machine learning roles. Strong proficiency in Python (pandas, scikit-learn, NumPy, TensorFlow/PyTorch) and SQL. Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Solid understanding of data structures, algorithms, and statistical concepts. Hands-on experience in NLP, time series forecasting, recommender systems, or computer vision is a plus. Strong communication and storytelling skills, with the ability to influence decision-making. Experience with version control (Git), CI/CD pipelines, and ML lifecycle management tools (MLflow, Airflow, etc.) is desirable. Preferred Qualifications: Prior experience in industries like finance, healthcare, retail, telecom, or manufacturing. Experience working with large-scale data processing frameworks (e.g., Spark, Hadoop). Knowledge of generative AI or LLM-based applications is a bonus.

About the Role We’re looking for an experienced AI Developer with hands-on expertise in Large Language Models (LLMs) , Azure AI services , and end-to-end ML pipeline deployment . If you’re passionate about building scalable AI solutions, integrating document intelligence, and deploying models in production using Azure, this role is for you. 💡 Key Responsibilities Design and develop AI applications leveraging LLMs (e.g., GPT, BERT) for tasks like summarization, classification, and document understanding Implement solutions using Azure Document Intelligence to extract structured data from forms, invoices, and contracts Train, evaluate, and tune ML models using Scikit-learn, XGBoost , or PyTorch Build ML pipelines and workflows using Azure ML , MLflow , and integrate with CI/CD tools Deploy models to production using Azure ML endpoints , containers, or Azure Functions for real-time AI workflows Write clean, efficient, and scalable code in Python and manage code versioning using Git Work with structured and unstructured data from SQL/NoSQL databases and Data Lakes Ensure performance monitoring and logging for deployed models ✅ Skills & Experience Required Proven experience with LLMs and Prompt Engineering (e.g., GPT, BERT) Hands-on with Azure Document Intelligence for OCR and data extraction Solid background in ML model development, evaluation , and hyperparameter tuning Proficient in Azure ML Studio , model registry , and automated ML workflows Familiar with MLOps tools such as Azure ML pipelines, MLflow , and CI/CD practices Experience with Azure Functions for building serverless, event-driven AI apps Strong coding skills in Python ; familiarity with libraries like NumPy, Pandas, Scikit-learn, Matplotlib Working knowledge of SQL/NoSQL databases and Data Lakes Proficiency with Azure DevOps , Git version control, and testing frameworks Show more Show less

Role Overview We're looking for a talented Machine Learning Engineer with 3+ years of experience to join our growing AI team. This role will play a central part in developing our real-time feedback engine, integrating and fine-tuning LLMs, and spearheading the training and deployment of custom and small language models (SLMs). Key Responsibilities Build and deploy scalable real-time inference systems using FastAPI and AWS. Fine-tune and integrate large language models (LLMs) like Claude 3.5 Sonnet via Amazon Bedrock. Lead or contribute to the training, fine-tuning, and evaluation of proprietary Small Language Models (SLMs). Build ML pipelines for preprocessing multimodal data (audio, transcript, slides). Collaborate with backend, design, and product teams to bring intelligent features into production. Optimize models for speed, efficiency, and edge/cloud deployment. Contribute to MLOps infrastructure for versioning, deployment, and monitoring of models. Required Qualifications 3+ years of experience in applied ML, including model deployment and training. Strong proficiency in Python, PyTorch, Transformers, and model training frameworks. Experience deploying APIs using FastAPI and integrating models in production. Experience fine-tuning LLMs (e.g., OpenAI, Claude, Mistral) and SLMs for specific downstream tasks. Familiarity with AWS services (S3, Bedrock, Lambda, SageMaker). Strong grasp of data pipelines, performance metrics, and model evaluation. Comfort working with multimodal datasets (text, audio, visual). Bonus Points Experience with Whisper, TTS systems (e.g., Polly), or audio signal processing. Background in building or fine-tuning SLMs for performance-constrained environments. Familiarity with MLOps tooling (MLflow, Weights & Biases, DVC). Experience with Redis, WebSockets, or streaming data systems. Perks and Benefits Attractive remuneration (competitive with market, based on experience and potential). Fully remote work – we’re a truly distributed team. Flexible working hours – we value output over clocking in. Health & wellness perks, learning stipends, and regular team retreats. Opportunity to work closely with passionate founders and contribute from Day 1. Be a core part of a fast-growing, high-impact startup with a mission to transform education. We look forward to receiving your application! Show more Show less

P-1346 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. Databricks Mosaic AI offers a unique data-centric approach to building enterprise-quality, Machine Learning and Generative AI solutions, enabling organizations to securely and cost-effectively own and host ML and Generative AI models, augmented or trained with their enterprise data. And we're only getting started in Bengaluru , India - and currently in the process of setting up 10 new teams from scratch ! The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialisation strategies, timely & accurate billing, cost optimisation tools, intelligent resource usage controls, and cutting-edge engineering. We provide a seamless and consistent experience set of platforms for all Databricks products to reach customers. As one of the first engineers for Money at Databricks India , you will be key to building a base for one of Databricks’ most central engineering teams . You will own critical components that form the backbone of our products, starting with Databricks’ resource admission control and usage governance infrastructure . Your role is crucial in helping bring diverse business needs together, including abuse prevention, product commercialisation motions, and reliable product availability at scale. You will work closely with infrastructure as well as product teams in bringing critical governance functionality to Databricks customers. The Impact You Will Have Own Money systems and services that govern usage of all Databricks products and offerings. Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection. Collaborate with platform and product teams to develop and implement innovative infrastructure that scales to meet evolving needs. Provide leadership in long-term vision and requirements development for Databricks products, in partnership with our engineering teams. Represent Databricks at academic and industrial conferences & events. What We Look For BS/MS/PhD in Computer Science, or a related field 12+ years of production level experience in one of: Java, Scala, C++, or similar language. Comfortable working towards a multi-year vision with incremental deliverables. Proven track record in architecting, developing, deploying, and operating large scale distributed systems. Experience with software security and systems that handle sensitive data. Demonstrated leadership skills and the ability to lead across functional and organizational boundaries. A proactive approach and a passion for delivering high-quality solutions Experience with cloud technologies, e.g. AWS, Azure, GCP, Docker, Kubernetes. 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

P-1347 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. Networking Infrastructure is a core part of the platform that powers all our data and AI products. The platform also powers key enterprise security features used by customers across all our products to build connectivity solutions to cloud resources and prevent data exfiltration. And we're setting up the team from scratch in Bengaluru , India. We are seeking an experienced Senior Software Engineers with a networking background to join the Networking Infrastructure team. As one of the seed members of the Bangalore site, you will be focussing on building new backend connectivity services that powers millions of VMs running on Databricks. You will also be leading the design and development of new services that powers the connectivity between our control plane and compute plane. This new platform enables Databricks to increase scalability of our compute plane while also efficiently use cloud resources. You will work closely with cross-functional teams, including product management, operations, and other engineering teams, to ensure the delivery of robust, scalable, and efficient networking systems. This is an excellent opportunity for a hands-on leader who thrives in a fast-paced environment and is passionate about solving novel multi-cloud and distributed systems challenges. What We Look For 8+ years of production level experience in one of: Python, Java, Scala, C++, or similar language 4+ years of experience developing large-scale distributed systems from scratch Experience working on a SaaS platform or with Service-Oriented Architectures. Extensive experience working in the Networking domain 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

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day. We have 3.44 PB of RAM deployed across our fleet of C* servers - and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About The Role The charter of the Data + ML Platform team is to harness all the data that is ingested and cataloged within the Data LakeHouse for exploration, insights, model development, ML Engineering and Insights Activation. This team is situated within the larger Data Platform group, which serves as one of the core pillars of our company. We process data at a truly immense scale. Our processing is composed of various facets including threat events collected via telemetry data, associated metadata, along with IT asset information, contextual information about threat exposure based on additional processing, etc. These facets comprise the overall data platform, which is currently over 200 PB and maintained in a hyper scale Data Lakehouse, built and owned by the Data Platform team. The ingestion mechanisms include both batch and near real-time streams that form the core Threat Analytics Platform used for insights, threat hunting, incident investigations and more. As an engineer in this team, you will play an integral role as we build out our ML Experimentation Platform from the ground up. You will collaborate closely with Data Platform Software Engineers, Data Scientists & Threat Analysts to design, implement, and maintain scalable ML pipelines that will be used for Data Preparation, Cataloging, Feature Engineering, Model Training, and Model Serving that influence critical business decisions. You’ll be a key contributor in a production-focused culture that bridges the gap between model development and operational success. Future plans include generative AI investments for use cases such as modeling attack paths for IT assets. What You’ll Do Help design, build, and facilitate adoption of a modern Data+ML platform Modularize complex ML code into standardized and repeatable components Establish and facilitate adoption of repeatable patterns for model development, deployment, and monitoring Build a platform that scales to thousands of users and offers self-service capability to build ML experimentation pipelines Leverage workflow orchestration tools to deploy efficient and scalable execution of complex data and ML pipelines Review code changes from data scientists and champion software development best practices Leverage cloud services like Kubernetes, blob storage, and queues in our cloud first environment What You’ll Need B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field and 7 + years related experience; or M.S. with 5+ years of experience; or Ph.D with 6+ years of experience. 3+ years experience developing and deploying machine learning solutions to production. Familiarity with typical machine learning algorithms from an engineering perspective (how they are built and used, not necessarily the theory); familiarity with supervised / unsupervised approaches: how, why, and when and labeled data is created and used 3+ years experience with ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI etc. Experience building data platform product(s) or features with (one of) Apache Spark, Flink or comparable tools in GCP. Experience with Iceberg is highly desirable. Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow, etc.) Production experience with infrastructure-as-code tools such as Terraform, FluxCD Expert level experience with Python; Java/Scala exposure is recommended. Ability to write Python interfaces to provide standardized and simplified interfaces for data scientists to utilize internal Crowdstrike tools Expert level experience with CI/CD frameworks such as GitHub Actions Expert level experience with containerization frameworks Strong analytical and problem solving skills, capable of working in a dynamic environment Exceptional interpersonal and communication skills. Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes. Experience With The Following Is Desirable Go Iceberg Pinot or other time-series/OLAP-style database Jenkins Parquet Protocol Buffers/GRPC VJ1 Benefits Of Working At CrowdStrike Remote-friendly and flexible work culture Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Resource Groups, geographic neighbourhood groups and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at recruiting@crowdstrike.com for further assistance. Show more Show less

As a global leader in cybersecurity, CrowdStrike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day. We have 3.44 PB of RAM deployed across our fleet of C* servers - and this traffic is growing daily. Our customers span all industries, and they count on CrowdStrike to keep their businesses running, their communities safe and their lives moving forward. We’re also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. We’re always looking to add talented CrowdStrikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters? The future of cybersecurity starts with you. About The Role The charter of the Data + ML Platform team is to harness all the data that is ingested and cataloged within the Data LakeHouse for exploration, insights, model development, ML Engineering and Insights Activation. This team is situated within the larger Data Platform group, which serves as one of the core pillars of our company. We process data at a truly immense scale. Our processing is composed of various facets including threat events collected via telemetry data, associated metadata, along with IT asset information, contextual information about threat exposure based on additional processing, etc. These facets comprise the overall data platform, which is currently over 200 PB and maintained in a hyper scale Data Lakehouse, built and owned by the Data Platform team. The ingestion mechanisms include both batch and near real-time streams that form the core Threat Analytics Platform used for insights, threat hunting, incident investigations and more. As an engineer in this team, you will play an integral role as we build out our ML Experimentation Platform from the ground up. You will collaborate closely with Data Platform Software Engineers, Data Scientists & Threat Analysts to design, implement, and maintain scalable ML pipelines that will be used for Data Preparation, Cataloging, Feature Engineering, Model Training, and Model Serving that influence critical business decisions. You’ll be a key contributor in a production-focused culture that bridges the gap between model development and operational success. Future plans include generative AI investments for use cases such as modeling attack paths for IT assets. What You’ll Do Help design, build, and facilitate adoption of a modern Data+ML platform Modularize complex ML code into standardized and repeatable components Establish and facilitate adoption of repeatable patterns for model development, deployment, and monitoring Build a platform that scales to thousands of users and offers self-service capability to build ML experimentation pipelines Leverage workflow orchestration tools to deploy efficient and scalable execution of complex data and ML pipelines Review code changes from data scientists and champion software development best practices Leverage cloud services like Kubernetes, blob storage, and queues in our cloud first environment What You’ll Need B.S. in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field and 7 + years related experience; or M.S. with 5+ years of experience; or Ph.D with 6+ years of experience. 3+ years experience developing and deploying machine learning solutions to production. Familiarity with typical machine learning algorithms from an engineering perspective (how they are built and used, not necessarily the theory); familiarity with supervised / unsupervised approaches: how, why, and when and labeled data is created and used 3+ years experience with ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI etc. Experience building data platform product(s) or features with (one of) Apache Spark, Flink or comparable tools in GCP. Experience with Iceberg is highly desirable. Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow, etc.) Production experience with infrastructure-as-code tools such as Terraform, FluxCD Expert level experience with Python; Java/Scala exposure is recommended. Ability to write Python interfaces to provide standardized and simplified interfaces for data scientists to utilize internal Crowdstrike tools Expert level experience with CI/CD frameworks such as GitHub Actions Expert level experience with containerization frameworks Strong analytical and problem solving skills, capable of working in a dynamic environment Exceptional interpersonal and communication skills. Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes. Experience With The Following Is Desirable Go Iceberg Pinot or other time-series/OLAP-style database Jenkins Parquet Protocol Buffers/GRPC VJ1 Benefits Of Working At CrowdStrike Remote-friendly and flexible work culture Market leader in compensation and equity awards Comprehensive physical and mental wellness programs Competitive vacation and holidays for recharge Paid parental and adoption leaves Professional development opportunities for all employees regardless of level or role Employee Resource Groups, geographic neighbourhood groups and volunteer opportunities to build connections Vibrant office culture with world class amenities Great Place to Work Certified™ across the globe CrowdStrike is proud to be an equal opportunity employer. We are committed to fostering a culture of belonging where everyone is valued for who they are and empowered to succeed. We support veterans and individuals with disabilities through our affirmative action program. CrowdStrike is committed to providing equal employment opportunity for all employees and applicants for employment. The Company does not discriminate in employment opportunities or practices on the basis of race, color, creed, ethnicity, religion, sex (including pregnancy or pregnancy-related medical conditions), sexual orientation, gender identity, marital or family status, veteran status, age, national origin, ancestry, physical disability (including HIV and AIDS), mental disability, medical condition, genetic information, membership or activity in a local human rights commission, status with regard to public assistance, or any other characteristic protected by law. We base all employment decisions--including recruitment, selection, training, compensation, benefits, discipline, promotions, transfers, lay-offs, return from lay-off, terminations and social/recreational programs--on valid job requirements. If you need assistance accessing or reviewing the information on this website or need help submitting an application for employment or requesting an accommodation, please contact us at recruiting@crowdstrike.com for further assistance. Show more Show less

Job Summary: We are looking for highly motivated and analytical Machine Learning Engineers with 1–3 years of experience in building scalable, production-ready AI/ML models. This role involves working on complex business problems using advanced ML/DL techniques across domains such as Natural Language Processing (NLP), Computer Vision, Time Series Forecasting, and Generative AI. You will be responsible for end-to-end model development, deployment, and performance tracking while collaborating with cross-functional teams including data engineering, DevOps, and product. Location: Noida / Gurugram / Indore / Bengaluru / Pune / Hyderabad Experience: 1–3 Years Education: BE / B.Tech / M.Tech / MCA / M.Com Key Responsibilities: Model Development & Experimentation Design and build machine learning models for NLP, computer vision, and time series prediction using supervised, unsupervised, and deep learning techniques. Conduct experiments to improve model performance via architectural modifications, hyperparameter tuning, and feature selection. Apply statistical analysis to validate and interpret model results. Evaluate models using appropriate metrics (e.g., accuracy, precision, recall, F1-score, AUC-ROC). Data Handling & Feature Engineering Process large structured and unstructured datasets using Python, Pandas, and DataFrame APIs. Perform feature extraction, transformation, and selection tailored to specific ML problems. Implement data augmentation and enrichment techniques to enhance training quality. Model Deployment & Productionization Deploy trained models to production environments using cloud platforms such as AWS (especially SageMaker). Containerize models using Docker and orchestrate deployments with Kubernetes. Implement monitoring, logging, and automated retraining pipelines for model health tracking. Collaboration & Innovation Collaborate with data engineers and architects to ensure smooth data flow and infrastructure alignment. Explore and adopt cutting-edge AI/ML methodologies and GenAI frameworks (e.g., LangChain, GPT-3). Contribute to documentation, versioning, and knowledge-sharing across teams. Drive innovation and continuous improvement in AI/ML delivery and engineering practices. Mandatory Technical Skills: Languages & Tools: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) Model Development: Deep Learning, NLP, Time Series, Computer Vision Cloud Platforms: AWS (especially SageMaker) Model Deployment: Docker, Kubernetes, REST APIs ML Ops: Model monitoring, performance logging, CI/CD Frameworks: LangChain (for GenAI), Transformers, Hugging Face Preferred / Good to Have: Experience with Foundation Model tuning and prompt engineering Hands-on with Generative AI (GPT-3/4, OpenAI APIs, LangChain integrations) Certifications: AWS Certified Machine Learning – Specialty Experience with version control (Git), and experiment tracking tools (MLflow, Weights & Biases) Soft Skills: Excellent communication and presentation abilities Strong analytical and problem-solving mindset Ability to work in collaborative, fast-paced environments Curiosity to learn emerging technologies and apply them to real-world problems Show more Show less

Job Title: AI/ML Developer (5 Years Experience) Location : Remote Job Type : Full-time Experience:5 Year Job Summary: We are looking for an experienced AI/ML Developer with at least 5 years of hands-on experience in designing, developing, and deploying machine learning models and AI-driven solutions. The ideal candidate should have strong knowledge of machine learning algorithms, data preprocessing, model evaluation, and experience with production-level ML pipelines. Key Responsibilities Model Development : Design, develop, train, and optimize machine learning and deep learning models for classification, regression, clustering, recommendation, NLP, or computer vision tasks. Data Engineering : Work with data scientists and engineers to preprocess, clean, and transform structured and unstructured datasets. ML Pipelines : Build and maintain scalable ML pipelines using tools such as MLflow, Kubeflow, Airflow, or SageMaker. Deployment : Deploy ML models into production using REST APIs, containers (Docker), or cloud services (AWS/GCP/Azure). Monitoring and Maintenance : Monitor model performance and implement retraining pipelines or drift detection techniques. Collaboration : Work cross-functionally with data scientists, software engineers, and product managers to integrate AI capabilities into applications. Research and Innovation : Stay current with the latest advancements in AI/ML and recommend new techniques or tools where applicable. Required Skills & Qualifications Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Minimum 5 years of experience in AI/ML development. Proficiency in Python and ML libraries such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM. Strong understanding of statistics, data structures, and ML/DL algorithms. Experience with cloud platforms (AWS/GCP/Azure) and deploying ML models in production. Experience with CI/CD tools and containerization (Docker, Kubernetes). Familiarity with SQL and NoSQL databases. Excellent problem-solving and communication skills. Preferred Qualifications Experience with NLP frameworks (e.g., Hugging Face Transformers, spaCy, NLTK). Knowledge of MLOps best practices and tools. Experience with version control systems like Git. Familiarity with big data technologies (Spark, Hadoop). Contributions to open-source AI/ML projects or publications in relevant fields. Show more Show less

osition: Data Scientist Location: Chennai, India (Work from Office) Experience: 2–5 years About the Opportunity: Omnihire is seeking a Data Scientist to join a leading AI-driven data‐solutions company. As part of the Data Consulting team, you’ll collaborate with scientists, IT, and engineering to solve high-impact problems and deliver actionable insights. Key Responsibilities: Analyze large, structured and unstructured datasets (SQL, Hadoop/Spark) to extract business-critical insights Build and validate statistical models (regression, classification, time-series, segmentation) and machine-learning algorithms (Random Forest, Boosting, SVM, KNN) Develop deep-learning solutions (CNN, RNN, LSTM, transfer learning) and apply NLP techniques (tokenization, stemming/lemmatization, NER, LSA) Write production-quality code in Python and/or R using libraries (scikit-learn, TensorFlow/PyTorch, pandas, NumPy, NLTK/spaCy) Collaborate with cross-functional teams to scope requirements, propose analytics solutions, and present findings via clear visualizations (Power BI, Matplotlib) Own end-to-end ML pipelines: data ingestion → preprocessing → feature engineering → model training → evaluation → deployment Contribute to solution proposals and maintain documentation for data schemas, model architectures, and experiment tracking (Git, MLflow) Required Qualifications: Bachelor’s or Master’s in Computer Science, Statistics, Mathematics, Data Science, or a related field 2–5 years of hands-on experience as a Data Scientist (or similar) in a data-driven environment Proficiency in Python and/or R for statistical modeling and ML Strong SQL skills and familiarity with Big Data platforms (e.g., Hadoop, Apache Spark) Demonstrated experience building, validating, and deploying ML/DL models in production or staging Excellent problem-solving skills, attention to detail, and ability to communicate technical concepts clearly Self-starter who thrives in a collaborative, Agile environment Nice-to-Have: Active GitHub/Kaggle portfolio showcasing personal projects or contributions Exposure to cloud-based ML services (Azure ML Studio, AWS SageMaker) and containerization (Docker) Familiarity with advanced NLP frameworks (e.g., Hugging Face Transformers) or production monitoring tools (Azure Monitor, Prometheus) Why Join? Work on high-impact AI/ML projects that drive real business value Rapid skill development with exposure to cutting-edge technologies Collaborative, Agile culture with mentorship from senior data scientists Competitive compensation package and comprehensive benefits Show more Show less

About Amgen Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Data Scientist What You Will Do The Global Quality Analytics and Innovation team leads the digital transformation and innovation effort throughout Amgen’s Quality organization. We are at the forefront of developing and rolling out data-centric digital tools, employing automation, artificial intelligence (AI), and generative AI to drive end-to-end quality transformation. We are seeking a highly motivated and experienced Data Scientist with a strong background in Generative AI, Large Language Models (LLMs), and MLOps, along with an understanding for Quality in regulated environments (e.g., GxP). This role will play a key part in designing, developing, and deploying scalable AI/ML solutions to drive innovation, efficiency, and regulatory compliance across the organization. You will collaborate with cross-functional teams, including software engineers, data engineers, business stakeholders, and quality professionals to deliver AI-driven capabilities that support strategic business objectives. The ideal candidate is an analytical thinker with excellent technical depth, communication skills, and the ability to thrive in a fast-paced, agile environment. Key Responsibilities Design, build, and deploy generative AI and LLM-based applications using frameworks such as LangChain, LlamaIndex, and others. Engineer reusable and effective prompts for LLMs like OpenAI GPT-4, Anthropic Claude, etc. Develop and maintain evaluation metrics and frameworks for prompt engineering. Conduct data quality assessments, data cleansing, and ingestion of unstructured documents into vector databases. Build retrieval algorithms for relevant data identification to support LLMs and AI applications. Ensure AI/ML development complies with GxP and other regulatory standards, fostering a strong Quality culture. Partner with global and local teams to support regulatory inspection readiness and future technological capabilities in AI. Share insights and findings with team members in an Agile (SAFe) environment. What We Expect Of You Basic Qualifications: Master’s degree and 2 – 4 years of experience in Software Engineering, Data Science, or ML Engineering or Bachelor’s degree and 3 to 5 years of experience in Software Engineering, Data Science, or ML Engineering or Diploma and 7 to 9 years of experience in Software Engineering, Data Science, or ML Engineering Preferred Qualifications: Experience in developing and deploying LLM applications. Strong foundation in ML algorithms, data science workflows, and NLP. Expertise in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with MLOps tools (e.g., MLflow, CI/CD, version control). Experience with cloud platforms (AWS, Azure, GCP) and tools like Spark, Databricks. Understanding of RESTful APIs and frameworks like FastAPI. Experience with BI and visualization tools (e.g., Tableau, Streamlit, Dash). Knowledge of GxP compliance and experience working in regulated environments. Strong communication skills with the ability to explain complex topics to diverse audiences. High degree of initiative, self-motivation, and ability to work in global teams. What You Can Expect Of Us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation. Show more Show less

Techvantage.ai is a next-generation technology and product engineering company at the forefront of innovation in Generative AI, Agentic AI , and autonomous intelligent systems . We build intelligent, cutting-edge solutions designed to scale and evolve with the future of artificial intelligence. Role Overview: We are looking for a skilled and versatile AI Infrastructure Engineer (DevOps/MLOps) to build and manage the cloud infrastructure, deployment pipelines, and machine learning operations behind our AI-powered products. You will work at the intersection of software engineering, ML, and cloud architecture to ensure that our models and systems are scalable, reliable, and production-ready. Key Responsibilities: Design and manage CI/CD pipelines for both software applications and machine learning workflows. Deploy and monitor ML models in production using tools like MLflow, SageMaker, Vertex AI, or similar. Automate the provisioning and configuration of infrastructure using IaC tools (Terraform, Pulumi, etc.). Build robust monitoring, logging, and alerting systems for AI applications. Manage containerized services with Docker and orchestration platforms like Kubernetes . Collaborate with data scientists and ML engineers to streamline model experimentation, versioning, and deployment. Optimize compute resources and storage costs across cloud environments (AWS, GCP, or Azure). Ensure system reliability, scalability, and security across all environments. Requirements: 5+ years of experience in DevOps, MLOps , or infrastructure engineering roles. Hands-on experience with cloud platforms ( AWS, GCP, or Azure ) and services related to ML workloads. Strong knowledge of CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI). Proficiency in Docker , Kubernetes , and infrastructure-as-code frameworks. Experience with ML pipelines , model versioning, and ML monitoring tools. Scripting skills in Python , Bash , or similar for automation tasks. Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, CloudWatch, etc.). Understanding of ML lifecycle management and reproducibility. Preferred Qualifications: Experience with Kubeflow , MLflow , DVC , or Triton Inference Server . Exposure to data versioning , feature stores , and model registries . Certification in AWS/GCP DevOps or Machine Learning Engineering is a plus. Background in software engineering, data engineering, or ML research is a bonus. What We Offer: Work on cutting-edge AI platforms and infrastructure Cross-functional collaboration with top ML, research, and product teams Competitive compensation package – no constraints for the right candidate Show more Show less

Company Description Winbold is a startup working on a AI driven investment platform. Job Description This requires immediate joining. Do not apply if you have notice period. We are looking for a very motivated Data Science and Machine Learning Engineer with hands-on experience in feature engineering, model training and building models that run and provide real-time predictions and forecasts. The candidate must be well versed with the following: ML Packages - sklean, xgboost, timeseries models Feature engineering and feature stores MLFlow for Model experimentation Model visualization Model deployment in Cloud and in hosted environments at scale For immediate consideration you can send email to me directly with a note on why you think you are the better suited for this role at madhu at winbolddatasystems.com Qualifications We dont care what degree you have or if you have one. We want a hands-on developer who can get shit done. Additional Information All your information will be kept confidential according to EEO guidelines. Show more Show less

droppGroup is hiring an exceptionally capable AI Engineer with deep, practical expertise in generative AI and natural language processing (NLP). This role is not for generalists, we are looking for specialists who can operate across the full AI lifecycle: from research implementation to real-time production deployment. You must bring a disciplined engineering mindset, state-of-the-art awareness, and hands-on experience with training, fine-tuning, and deploying large language models at scale. Responsibilities Design and fine-tune large transformer models for complex generative tasks including chat, summarization, and semantic understanding. Build LLM-based systems using advanced prompt engineering, retrieval-augmented generation (RAG), and optimized inference. Own the development and optimization of model training pipelines using PyTorch, Hugging Face, DeepSpeed, and related frameworks. Deploy and maintain LLMs in high-performance production environments, optimizing for latency, cost, and stability. Conduct rigorous evaluation of models using benchmarks, human feedback, and automated testing. Manage end-to-end AI workflows with robust versioning, reproducibility, and observability using MLOps tooling. Implement scalable vector databases and semantic search infrastructure for embedding-based retrieval systems. Translate latest AI research into efficient, production-grade code—no research-only profiles. Size, allocate, and optimize compute resources (CPU/GPU/TPU) for large-scale training and inference. Establish strict testing, rollback, and fail-safe mechanisms for model deployment in live systems. Qualifications Minimum 3 years of focused experience building deep learning systems, with a proven track record in NLP and/or generative AI. Hands-on experience training and deploying transformer-based models (BERT, T5, GPT, LLaMA, etc.)—from scratch or via fine-tuning. Expert-level Python, with production-grade PyTorch skills (Tensor manipulation, gradient debugging, memory profiling, etc.). Demonstrated ability to work with multi-billion parameter models, and deploy them under real-world latency and throughput constraints. Deep understanding of language modeling, embeddings, attention mechanisms, tokenization strategies, and architectural tradeoffs. Ability to read, implement, and extend research papers into robust, testable, and efficient systems. Experience with AI infrastructure at scale, including distributed training, mixed precision, checkpointing, and A100-level GPU scheduling. Familiarity with vector databases (FAISS, Weaviate, Milvus) and hybrid search systems. Proficiency in MLOps tools (MLflow, Airflow, WandB, or similar) for model lifecycle management. Strong commitment to software engineering principles: code quality, version control, CI/CD, and modular design. Capacity to own AI systems end-to-end—from dataset preprocessing to online deployment and continuous improvement. droppGroup is an equal opportunity employer. We offer a competitive compensation structure and a fast-paced growth roadmap to all our teams. Show more Show less

Primary skills:Technology->OpenSystem->Python - OpenSystem Responsible for successful delivery of MLOps solutions and services in client consulting environments; Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client. Assist clients with operationalization metrics to track performance of ML Models Agile trained to manage team effort and track through JIRA High Impact Communication- Assesses the target audience need, prepares and practices a logical flow, answers audience questions appropriately and sticks to timeline. Technical knowledge- has expertise in cloud technologies, specifically MS Azure, and services with hands on coding to – Expertise in Object Oriented Python Programming with 6 -8 years’ experience. DevOps Working knowledge with implementation experience - 1 or 2 projects a minimum Hands-On MS Azure Cloud knowledge Understand and take requirements on Operationalization of ML Models from Data Scientist Help team with ML Pipelines from creation to execution List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup Assist team to coding standards (flake8 etc) Guide team to debug on issues with pipeline failures Engage with Business / Stakeholders with status update on progress of development and issue fix Automation, Technology and Process Improvement for the deployed projects Setup Standards related to Coding, Pipelines and Documentation Adhere to KPI / SLA for Pipeline Run, Execution Research on new topics, services and enhancements in Cloud Technologies Domain / Technical / Tools Knowledge: Object oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs Python programming with OOPs concept, SQL, XML, YAML, Bash, JSON, Pydantic models, Class based frameworks, Dependency injections FastAPI, Flask, Streamlit, Python, Azure API management, API Gateways, Traffic Manager, Load Balancers Nginx, Uvicorn, Gunicorn, Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts. Experience designing and implementing ML Systems & pipelines, MLOps practices and tools such a MLFlow, Kubernetes, etc. Exposure to event driven orchestration, Online Model deployment Contribute towards establishing best practices in MLOps Systems development Proficiency with data analysis tools (e.g., SQL, R & Python) High level understanding of database concepts/reporting & Data Science concepts Hands on experience in working with client IT/Business teams in gathering business requirement and converting into requirement for development team Experience in managing client relationship and developing business cases for opportunities Azure AZ-900 Certification with Azure Architect Good knowledge on software configuration management systems Strong business acumen, strategy and cross-industry thought leadership Awareness of latest technologies and Industry trends Education and Experience: Overall, 6 to 8 years of experience in Data driven software engineering with 3-5 years of experience designing, building and deploying enterprise AI or ML applications with at least 2 years of experience implementing full lifecycle ML automation using MLOps(scalable development to deployment of complex data science workflows) Bachelors or Master’s degree in Computer Science Engineering or equivalent Domain experience in Retail, CPG and Logistics etc. Azure Certified – DP100, AZ/AI900 Logical thinking and problem solving skills along with an ability to collaborate Two or three industry domain knowledge Understanding of the financial processes for various types of projects and the various pricing models available Client Interfacing skills Knowledge of SDLC and agile methodologies Project and Team management Show more Show less

Redefine the future of customer experiences. One conversation at a time. We're changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you're ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you're in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities: Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications: Education: Master's degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills: MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes: Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you're passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security - Provident Fund & Gratuity Wellness ‍ - Employee Assistance Program and comprehensive wellness initiatives Growth - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what's going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. #LI-SC1 #LI-Hybrid

WHO YOU ARE: A passionate and skilled Python, AI/ML Lead Engineer with 7+ years of experience. As a Python/AI Lead, you will oversee the development and implementation of machine learning models, AI-driven solutions, and data-driven products. You will guide a team of engineers and collaborate with cross-functional teams to ensure the timely and high-quality delivery of projects. If you thrive in a fast-paced environment and love solving complex problems using data and intelligent algorithms, we'd love to hear from you. WHAT YOU'LL DO: Lead the design, development, and deployment of Gen AI and machine learning solutions using Python. Provide technical guidance and mentorship to team members, ensuring code quality, best practices, and performance optimization. Collaborate with product managers, data scientists, and other stakeholders to define project requirements and objectives. Take ownership of the full software development lifecycle (SDLC), from design to deployment, maintenance, and optimization. Perform code reviews, write technical documentation, and maintain high standards of software quality. Stay up to date with the latest trends and advancements in AI, machine learning, and Python development. Identify and mitigate technical risks in projects while ensuring timely delivery. Foster a collaborative environment and promote knowledge sharing across the engineering team. WHAT YOU'LL NEED: 7+ years of professional experience in Python development, with at least 2 years in a technical leadership role. Strong hands-on experience with AI/ML frameworks, Gen AI LLMs and libraries such as TensorFlow, Scikit-learn, or Keras. Python – Strong hands-on experience. Machine Learning – Practical knowledge of supervised, unsupervised, and deep learning techniques. Generative AI – Experience working with LLMs or similar GenAI technologies. API Development – RESTful APIs and integration of ML models into production services. Databases – Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, etc.). Good to Have Skills: Cloud Platforms – Familiarity with AWS, Azure, or Google Cloud Platform (GCP). TypeScript/JavaScript – Frontend or full-stack exposure for ML product interfaces. Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, etc.) Exposure to containerization (Docker) and orchestration (Kubernetes) WHAT'S IN IT FOR YOU? At Zinnia, you collaborate with smart, creative professionals who are dedicated to delivering cutting-edge technologies, deeper data insights, and enhanced services to transform how insurance is done. Visit our website at www.zinnia.com for more information. Apply by completing the online application on the careers section of our website. We are an Equal Opportunity employer committed to a diverse workforce. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability

Summary At Novartis, innovation is at the heart of everything we do — and AI is a key enabler in how we reimagine medicine. As an Associate Director Solution Delivery – AI Products, you’ll lead the development and delivery of advanced AI solutions that transform commercial operations in the U.S. market. You will sit at the intersection of technology, data science, and business — owning the product lifecycle from discovery to deployment, while fostering a culture of experimentation, innovation, and continuous delivery. Working within the DD&T Commercial organization, you’ll turn novel ideas into production-ready products that deliver real-world impact. About The Role Key Responsibilities Product Strategy & Innovation Shape and own the product roadmap for AI solutions that power next-gen commercial capabilities — including intelligent targeting, omnichannel orchestration, and HCP engagement optimization. Drive innovation by scouting new AI technologies, validating ideas through MVPs and pilots, and scaling high-value solutions. Translate commercial objectives into actionable technical requirements and solution architectures. Technical Delivery & Solution Ownership Lead cross-functional teams (data science, data engineering, MLOps, digital product) to build, deploy, and operate production-grade AI solutions. Oversee technical delivery from data ingestion and model development to deployment, monitoring, and retraining. Ensure models are performant, scalable, secure, and seamlessly integrated into platforms such as CRM and content engines. Stakeholder Management & Business Alignment Partner with commercial stakeholders (field teams, marketing, analytics) to define needs, align priorities, and drive adoption. Act as a translator between business and technical teams — clearly communicating trade-offs, timelines, and value. Provide thought leadership and influence stakeholders at multiple levels, from working teams to senior leadership. Compliance & Responsible AI Ensure solutions align with Novartis standards and external regulations Embed ethical AI principles into product design — including fairness, transparency, and accountability. Core Technical Focus Areas AI/ML Development: Supervised learning, NLP, recommender systems, experimentation frameworks. Data Infrastructure: Scalable pipelines, real-time data ingestion, structured/unstructured healthcare data. MLOps: Model deployment, versioning, monitoring, and retraining workflows (MLflow, Airflow, SageMaker, etc.). Integration: REST/gRPC APIs, integration with CRM (e.g., Veeva), content platforms, and campaign engines. Cloud Platforms: AWS, Azure, or GCP environments for AI/ML workloads and data operations. What You’ll Bring 5+ years of product management experience, with 2+ years in AI/ML or data-centric product delivery. Strong technical foundation and experience working closely with engineering and data science teams. Demonstrated ability to deliver AI products from concept to production, including service ownership. Strong stakeholder management skills, with the ability to influence across technical and business domains. Experience in healthcare, life sciences, or other regulated environments is a plus. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Join our Novartis Network: Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards Show more Show less

We're Hiring: AI DevOps Engineer – ML, LLM & Cloud for Battery & Livestock Intelligence 📍 Hyderabad / Remote | 🧠 3–8 Years Experience 💼 Full-time | Deep Tech | AI-Driven IoT At Vanix Technologies , we’re solving real-world problems using AI built on top of IoT data — from predicting the health of electric vehicle batteries to monitoring livestock behavior with BLE sensors. We’re looking for a hands-on AI DevOps Engineer who understands not just how to build ML/DL models, but also how to turn them into intelligent cloud-native services . If you've worked on battery analytics or sensor-driven ML , and you're excited by the potential of LLMs + real-time IoT — this is for you. What You’ll Work On 🔋 EV Battery Intelligence Build models for SOH, true SOH, SOC, RUL prediction , thermal event detection, and high-risk condition classification. Ingest and process time-series data from BMS, CAN bus, GPS , and environmental sensors. Deliver analytics that plug into our BatteryTelematicsPro SaaS for OEMs and fleet customers. 🐄 Livestock Monitoring AI Analyze BLE sensor data from our cattle wearables (motion, temp, rumination proxies). Develop models for health anomaly detection, estrus prediction, movement patterns , and outlier behaviors. Power actionable insights for farmers via mobile dashboards and alerts. 🤖 Agentic AI & LLM Integration Chain ML outputs with LLMs (e.g., GPT-4, Claude) using LangChain or similar frameworks . Build AI assistants that summarize events, auto-generate alerts, and respond to user queries using both structured and ML-derived data. Support AI-powered explainability and insight generation layers on top of raw telemetry. ☁️ Cloud ML Engineering & DevOps Deploy models on AWS (Lambda, SageMaker, EC2, ECS, CloudWatch). Design and maintain CI/CD pipelines for data, models, and APIs. Optimize performance, cost, and scalability of cloud workloads. ✅ You Must Have Solid foundation in ML/DL for time-series / telemetry data Hands-on with PyTorch / TensorFlow / Scikit-learn / XGBoost Experience with battery analytics or sensor-based animal behavior prediction Understanding of LangChain / OpenAI APIs / LLM orchestration AWS fluency: Lambda, EC2, S3, SageMaker, CloudWatch Python APIs Nice to Have MLOps stack (MLFlow, DVC, W&B) BLE signal processing or CAN bus protocol parsing Prompt engineering or fine-tuning experience Exposure to edge-to-cloud model deployment Why Vanix Technologies? Because we're not another AI lab — we're a deep-tech company building production-ready AI platforms that interact with real devices in the field , used by farmers, OEMs, and EV fleets . You’ll work at the intersection of: IoT + AI + LLMs Hardware + Cloud Mission-critical data + Everyday impact Show more Show less

Required Skills & Qualifications: 4 to 12 years of experience in Data Science, Machine Learning, or AI. Proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch . Experience with ML lifecycle tools such as MLflow, Airflow, or SageMaker. Solid understanding of statistics, probability, and linear algebra . Experience working with structured and unstructured data (SQL, NoSQL, text, images, etc.). Familiarity with cloud platforms like AWS, Azure, or GCP. Strong problem-solving and analytical thinking skills.

Job Summary: We are looking for a highly motivated and analytical Data Scientist / Machine Learning (ML) Engineer / AI Specialist with 1.5 -2 years of experience in Health data analysis, particularly with data sourced from wearable devices such as smartwatches and fitness trackers. The ideal candidate will be proficient in developing data models, analyzing complex datasets, and translating insights into actionable strategies that enhance health-related applications. Key Responsibilities: Develop and implement data models tailored to health data from wearable devices. Stay updated on industry trends and emerging technologies in health data analytics. Ensure data integrity and security throughout the analysis process , correlations relevant to health metrics. Analyze large datasets to extract actionable insights using statistical methods and machine learning techniques. Develop, train, test, and deploy machine learning models for classification, regression, clustering, NLP, recommendation, or computer vision tasks. Collaborate with cross-functional teams including product, engineering, and domain experts to define problems and deliver solutions. Design and build scalable ML pipelines for model development and deployment. Conduct exploratory data analysis (EDA), data wrangling, feature engineering, and model validation. Monitor model performance in production and iterate based on feedback and data drift. Stay up to date with the latest research and trends in machine learning, deep learning, and AI. Document processes, code, and methodologies to ensure reproducibility and collaboration. Required Qualifications: Bachelor's or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or related field. 1.5-2 years of experience in data analysis, preferably within the health tech sector. Strong knowledge of Python or R and libraries such as NumPy, pandas, scikit-learn, TensorFlow, PyTorch, or XGBoost. Strong experience with data modeling, machine learning algorithms, and statistical analysis. Familiarity with health data privacy regulations (e.g., HIPAA) and data visualization tools (e.g., Tableau, Power BI). Proficiency in SQL and experience working with large-scale data systems (e.g., Spark, Hadoop, BigQuery, Snowflake). Ability to clearly communicate complex technical concepts to both technical and non-technical audiences. Experience with version control tools (e.g., Git) and ML pipeline tools (e.g., MLflow, Airflow, Kubeflow). Experience deploying models in cloud environments (AWS, GCP, Azure). Knowledge of NLP (e.g., Transformers, LLMs), computer vision, or reinforcement learning. Familiarity with MLOps, CI/CD for ML, and model monitoring tools. Experience - 1.5 - 2 years (Only Local Candidates) Location - Mohali Phase 8b Show more Show less

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

About Beatly.AI Beatly.AI is a fast-scaling AI startup transforming healthcare through neural network-powered innovation. Our mission is to build clinically meaningful, data-driven solutions that empower medical professionals and enhance patient outcomes. We are seeking an Senior AI/ML Team Engineer to drive both hands-on model development and technical leadership across our deep learning initiatives. About the Role As an Senior AI/ML Team Engineer , you will play a dual role: writing production-grade code, developing and deploying neural network models, while also leading a team of engineers through key initiatives. You’ll be responsible for full-lifecycle development of AI systems—from research and experimentation to scalable cloud deployment—and for shaping our infrastructure and team practices. Key Responsibilities Design and build advanced neural network models (CNNs, LSTMs, GRUs, autoencoders, time-series networks) for real-world healthcare applications. Lead the development of modular, reusable ML pipelines for training, validation, and inference. Actively contribute code and own model architecture, optimization, and deployment workflows. Architect cloud-ready, scalable ML systems using AWS/GCP/Azure, with containers (Docker) and orchestration (Kubernetes). Implement robust ML Ops processes including CI/CD pipelines, model versioning, monitoring, and rollback mechanisms. Collaborate with data, product, and engineering teams to define AI use cases and deliver end-to-end solutions. Guide and mentor a team of engineers—conduct code reviews, help troubleshoot, and support their development. Optimize compute resource usage (e.g., GPU scheduling, mixed precision, parallelism) for large-scale training jobs. Track and improve performance metrics (accuracy, latency, reliability), ensuring production-readiness of deployed models. Evaluate new techniques in neural networks (excluding LLMs) and assess their relevance for healthcare use cases. Skills & Qualifications 4+ years of experience in AI/ML engineering with a strong track record of shipping deep learning solutions. 1+ years of experience in leading or mentoring technical teams, while continuing to build and ship code. Strong proficiency in Python , with hands-on expertise in PyTorch , TensorFlow , or Keras . Deep understanding of neural network architectures for time-series, image, or signal-based tasks. Solid experience deploying models on cloud platforms (AWS/GCP/Azure), using tools like Docker, Kubernetes, and Terraform. Experience with ML pipeline tools (MLFlow, Airflow, DVC, Weights & Biases) and experiment tracking. Proficient in software engineering fundamentals, microservices, API integration, and scalable system design. Excellent written and verbal communication skills with a leadership mindset. Preferred Qualifications Experience with healthcare data: ECG, imaging, vitals, or clinical time-series. Familiarity with HIPAA, FDA, or healthcare compliance workflows. Background in distributed model training and GPU optimisation (e.g., Horovod, TorchElastic). Master’s or PhD in Computer Science, or related discipline. What We Offer Strategic leadership role with deep technical involvement. A mission-driven environment solving problems that matter. Real ownership over architecture, code, and team development. Excellent compensation with top-tier salary . Dynamic, collaborative team culture with space to innovate and grow. Apply Now If you're an experienced deep learning engineer ready to lead and build, and passionate about using neural networks to change the future of healthcare—we want to meet you. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less

Redefine the future of customer experiences. One conversation at a time. We’re changing the game with a first-of-its-kind, conversation-centric platform that unifies team collaboration and customer experience in one place. Powered by AI, built by amazing humans. Our culture is forward-thinking, customer-obsessed and built on an unwavering belief that connection fuels business and life; connections to our customers with our signature Amazing Service®, our products and services, and most importantly, each other. Since 2008, 100,000+ companies and 1M+ users rely on Nextiva for customer and team communication. If you’re ready to collaborate and create with amazing people, let your personality shine and be on the frontlines of helping businesses deliver amazing experiences, you’re in the right place. Build Amazing - Deliver Amazing - Live Amazing - Be Amazing We are looking for a visionary Head of Engineering (AI & ML) with extensive experience in leading AI/ML initiatives, team leadership, and end-to-end product delivery. This role combines strategic leadership with deep technical expertise to drive the development of advanced AI solutions, such as Agent Assist, IVA, Chatbots, Conversational Intelligence, and Data Visualization. You will work at the intersection of cutting-edge technology and business strategy, managing high-performing teams to deliver scalable, high-value AI products. Key Responsibilities Strategic Leadership Vision and Strategy: Partner with leadership to define AI product visions, success metrics, and strategic initiatives. Roadmap Development: Shape the medium and long-term AI product roadmap, aligning technical capabilities with business objectives. Emerging Trends: Serve as a thought leader, identifying and championing the adoption of emerging AI/ML trends and technologies. AI Product & Technical Delivery AI/ML Model Development: Oversee the training, fine-tuning, and deployment of advanced AI models, including NLP, ASR, TTS, and generative AI systems. Product Innovation: Drive the design and implementation of core AI/ML features to support intelligent automation and conversational experiences. Resource Management: Strategically plan and allocate team resources to meet roadmap goals and manage dependencies effectively. Scalability: Architect scalable AI systems with high availability, low latency, and adherence to SLAs. Engineering Leadership Technical Guidance: Provide hands-on technical leadership, diving into architecture, code, and design while managing the broader product delivery. Team Performance: Build and sustain an engineering rhythm that fosters high performance, knowledge sharing, and smooth execution. MLOps & Infrastructure: Establish scalable infrastructure and automated pipelines for model training, deployment, and performance monitoring. Team Development and Culture Mentorship: Act as a coach and mentor to foster technical growth and career development for team members. Inclusive Culture: Build a fun, inclusive, and supportive work environment that aligns with company values and encourages collaboration. Exemplify Leadership Principles: Inspire the team by modeling resilience, learning from failures, and celebrating the success of others. Cross-Functional Collaboration Partnerships: Collaborate with product management, design, and business stakeholders to ensure AI solutions meet market and regulatory requirements. Communication: Translate complex technical strategies into clear, actionable insights for both technical and non-technical stakeholders. Required Qualifications Education: Master’s degree in Applied Mathematics, Computer Science, or a related field. Experience: 10+ years in software engineering with expertise in AI/ML. Proven track record in leading teams to deliver AI products such as IVA, chatbots, or conversational intelligence. Hands-on experience with VoIP communications and real-time AI-driven solutions. Strong foundation in end-to-end AI product development and regulatory compliance. Demonstrated ability to evaluate and implement algorithmic solutions tailored to business use cases. Technical Skills: Deep knowledge of NLP, machine learning, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience deploying AI systems at scale using Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure). Expertise in optimization techniques like vLLM, quantization, and LoRA for high-performance inferencing. Proficiency in programming languages such as Python and experience building production-grade pipelines. Preferred Skills MLOps Expertise: Advanced knowledge of CI/CD pipelines, monitoring tools (MLflow, Airflow), and distributed training frameworks. Scalable Training Infrastructure: Hands-on experience with GPU/TPU workloads and frameworks like Horovod or DeepSpeed. Generative AI Expertise: Experience designing Retrieval-Augmented Generation (RAG) systems and fine-tuning large language models for domain-specific applications. Leadership Attributes Strong people management and mentoring skills with a proven ability to build high-performing teams. Ability to measure team impact, set clear goals, and drive collaboration across functions. Exceptional problem-solving and decision-making skills in ambiguous, high-impact scenarios. If you’re passionate about leading the development of transformative AI/ML solutions and want to make an organizational impact through innovative technologies, apply now to join our team! Total Rewards Our Total Rewards offerings are designed to allow our employees to take care of themselves and their families so they can be their best, in and out of the office. Our compensation packages are tailored to each role and candidate's qualifications. We consider a wide range of factors, including skills, experience, training, and certifications, when determining compensation. We aim to offer competitive salaries or wages that reflect the value you bring to our team. Depending on the position, compensation may include base salary and/or hourly wages, incentives, or bonuses. Medical 🩺 - Medical insurance coverage is available for employees, their spouse, and up to two dependent children with a limit of 500,000 INR, as well as their parents or in-laws for up to 300,000 INR. This comprehensive coverage ensures that essential healthcare needs are met for the entire family unit, providing peace of mind and security in times of medical necessity. Group Term & Group Personal Accident Insurance 💼 - Provides insurance coverage against the risk of death / injury during the policy period sustained due to an accident caused by violent, visible & external means. Coverage Type - Employee Only Sum Insured - 3 times of annual CTC with minimum cap of INR 10,00,000 Free Cover Limit - 1.5 Crore Work-Life Balance ⚖️ - 15 days of Privilege leaves per calendar year, 6 days of Paid Sick leave per calendar year, 6 days of Casual leave per calendar year. Paid 26 weeks of Maternity leaves, 1 week of Paternity leave, a day off on your Birthday, and paid holidays Financial Security💰 - Provident Fund & Gratuity Wellness 🤸‍ - Employee Assistance Program and comprehensive wellness initiatives Growth 🌱 - Access to ongoing learning and development opportunities and career advancement At Nextiva, we're committed to supporting our employees' health, well-being, and professional growth. Join us and build a rewarding career! Established in 2008 and headquartered in Scottsdale, Arizona, Nextiva secured $200M from Goldman Sachs in late 2021, valuing the company at $2.7B.To check out what’s going on at Nextiva, check us out on Instagram, Instagram (MX), YouTube, LinkedIn, and the Nextiva blog. Show more Show less