524 Mlops Jobs - Page 12

Job Title : Data Scientist - AI Integration & Orchestration. Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Job Title : Data Scientist - AI Integration & Orchestration. Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Job Summary : We are seeking a skilled Data Scientist with expertise in AI orchestration and embedded systems to support a sprint-based Agile implementation focused on integrating generative AI capabilities into enterprise platforms such as Slack, Looker, and Confluence. The ideal candidate will have hands-on experience with Gemini and a strong understanding of prompt engineering, vector databases, and orchestration infrastructure. Key Responsibilities : - Develop and deploy Slack-based AI assistants leveraging Gemini models. - Design and implement prompt templates tailored to enterprise data use cases (Looker and Confluence). - Establish and manage an embedding pipeline for Confluence documentation. - Build and maintain orchestration logic for prompt execution and data retrieval. - Set up API authentication and role-based access controls for integrated systems. - Connect and validate vector store operations (e.g., Pinecone, Weaviate, or Snowflake vector extension). - Contribute to documentation, internal walkthroughs, and user acceptance testing planning. - Participate in Agile ceremonies including daily standups and sprint demos. Required Qualifications : - Proven experience with Gemini and large language model deployment in production environments. - Proficiency in Python, orchestration tools, and prompt engineering techniques. - Familiarity with vector database technologies and embedding workflows. - Experience integrating APIs for data platforms such as Looker and Confluence. - Strong understanding of access control frameworks and enterprise-grade authentication. - Demonstrated success in Agile, sprint-based project environments. Preferred Qualifications : - Experience working with Slack app development and deployment. - Background in MLOps, LLMOps, or AI system orchestration at scale. - Excellent communication skills and ability to work in cross-functional teams.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Key Responsibilities : - Conduct feature engineering, data analysis, and data exploration to extract valuable insights. - Develop and optimize Machine Learning models to achieve high accuracy and performance. - Design and implement Deep Learning models, including Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Reinforcement Learning techniques. - Handle real-time imbalanced datasets and apply appropriate techniques to improve model fairness and robustness. - Deploy models in production environments and ensure continuous monitoring, improvement, and updates based on feedback. - Collaborate with cross-functional teams to align ML solutions with business goals. - Utilize fundamental statistical knowledge and mathematical principles to ensure the reliability of models. - Bring in the latest advancements in ML and AI to drive innovation. Requirements : - 4-5 years of hands-on experience in Machine Learning and Deep Learning. - Strong expertise in feature engineering, data exploration, and data preprocessing. - Experience with imbalanced datasets and techniques to improve model generalization. - Proficiency in Python, TensorFlow, Scikit-learn, and other ML frameworks. - Strong mathematical and statistical knowledge with problem-solving skills. - Ability to optimize models for high accuracy and performance in real-world scenarios. Preferred Qualifications : - Experience with Big Data technologies (Hadoop, Spark, etc.) - Familiarity with containerization and orchestration tools (Docker, Kubernetes). - Experience in automating ML pipelines with MLOps practices. - Experience in model deployment using cloud platforms (AWS, GCP, Azure) or MLOps tools.

Position - MLOPS Engineer / Lead Experience - 5 to 15 years Location - Bangalore Job description Key Responsibilities Data Architecture Design: Lead the design and implementation of scalable data architectures that support both data processing and machine learning workflows. ETL Development: Develop and manage ETL (Extract, Transform, Load) processes to ensure efficient data ingestion, cleaning, and transformation for machine learning applications. Model Development: Collaborate with data scientists to design, build, and deploy machine learning models that address business needs and improve operational efficiency. Performance Monitoring: Monitor the performance of data pipelines and machine learning models in production, making necessary adjustments to optimize performance and accuracy. Team Leadership: Mentor and guide a team of data engineers and machine learning engineers, fostering a collaborative environment focused on continuous improvement. Cross-Functional Collaboration: Work closely with product managers, software engineers, UI/UX and other stakeholders to align data initiatives with business objectives. Required Skills Technical Proficiency: Strong programming skills in languages such as Python; experience with big data technologies is essential. Machine Learning Knowledge: Understanding of machine learning algorithms, frameworks, and best practices for model development and deployment. Data Management Expertise: Proficiency in database management systems (SQL and NoSQL), data modeling, and ETL tools. Cloud Computing Experience: Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying data solutions and machine learning models. Leadership Skills: Excellent communication and interpersonal skills to lead teams effectively and collaborate across departments

Design and implement AI/ML architectures, lead innovation, ensure compliance, and mentor teams to deliver scalable AI-driven solutions in healthcare. Soft Skills: Strong leadership, communication, and collaboration abilities. Required Candidate profile 10+ yrs in soft architecture with at least 5 yrs in AI/ML. Proficiency in Python, deep learning frameworks (TensorFlow, PyTorch), & cloud platforms (AWS, Azure, GCP). Relevant AI/ML certi are advant.

Role - Machine Learning Engineer Required Skills & Experience 3+ years of hands-on experience in building, training, and deploying machine learning models in a professional, production-oriented setting. Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts. Proven expertise in data blending, transformation, and feature engineering , adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data. Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable. Proficiency in programming languages commonly used in data science (e.g., Python is preferred, R). Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like Deep Learning, Natural Language Processing (NLP), or Computer Vision . Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch ). Familiarity with MLOps tools and practices , including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines. Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs. Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development. Interested candidates share cv to dikshith.nalapatla@motivitylabs.com

Experience with MLOps practices and tools (Kubeflow, Kubernetes, LakeFS). experience of the current AI landscape and it’s applications. Proficiency in Python Salary : upto 26lpa Location : Gurugram

The Opportunity As a Nutanix Ready Engineer you are responsible for working with Nutanix ISV technology partners to help them test and validate their products and solutions on the Nutanix platform. This position will require working closely with Nutanix Product Management, Engineering, Support and Sales. The ideal candidate will have the opportunity to work on various projects and pioneering industry technologies in Cloud Native, AI and Hybrid Cloud. It is a forward thinking and strategic role which will require interacting with cross functional teams within Nutanix and be the voice of our Technology Partner and ability to influence change. Your role: Engage with Technology Partners to understand and clearly articulate technical use cases for Nutanix Platform.. Engage with PM and Engineering, QA to build validation test kits for joint solutions. Assist the partner with testing and validating the solution in accordance with Nutanix best practices and guidelines. Setup test bed, design test methodology and execute tests to determine compatibility of ISVs solution with Nutanix. Contemplate and develop automation tests to make validations robust, accurate and reduce execution time. Document and communicate technical details around the joint solution with extended teams (Sales, Support and Consulting) within the organization. Become an expert on one or more Nutanix Products/technologies and mature as an SME for Nutanix partner ecosystem. What You Will Bring: Masters university degree in Computer Science, Computer Engineering or related field with an industry work experience of 8-10 years or above Strong industry experience in development and automation in Python and APIs. Experience of technologies DevOps, Containers & Kubernetes. Knowledge or experience of MLOps, AI Infrastructure is a plus AWS or Azure cloud industry certifications and experience Knowledge of Nutanix technologies/platform is a plus but not a must. Strong analytical, problem solving and debugging skills. Excellent verbal and written communication skills

You will develop, optimize, and deploy state-of-the-art generative models for diverse applications, including text generation, image synthesis, and audio processing This role requires expertise in computer vision, machine learning, deep learning, and MLOps, with hands-on experience in GANs, VAEs, Transformers, and Diffusion Models You will actively contribute to building AI tools for CGI animation and VFX pipelines, enabling scalable, creative, and efficient workflows across departments including Asset Development, Rigging, Animation, Layout, Lighting, FX, Compositing, Editorial, and Rendering Design, develop, train, and optimize generative models (GANs, VAEs, Diffusion Models, Transformer Models) across text, image, audio, and video domains: 3D Reconstruction Human Pose Estimation Multimodal Learning Speech-Driven Animation Python and C++ for AI and pipeline integration

Hiring a Senior GenAI Engineer with 7-12 years of experience in Python, Machine Learning, and Large Language Models (LLMs) for a 6-month engagement based in Gurugram This hands-on role involves building intelligent systems using Langchain and RAG, developing agent workflows, and defining technical roadmaps The ideal candidate will be proficient in LLM architecture, prompt engineering, vector databases, and cloud platforms (AWS, Azure, GCP) The position demands strong collaboration skills, a system design mindset, and a focus on production-grade AI/ML solutions

What You'll Do: Build and maintain cloud deployment of ML models and surrounding infrastructure Contribute to infrastructure and process improvements for data collection, labeling, model development and deployment Design and implement R&D data engineering solutions for delivery of ML model value from device to cloud, including message payload design, data ingest and database architecture Help prepare and automate builds for device model deployment Assist on projects led by other team members via data processing, programming, monitoring of production applications, etc. Other duties as assigned. What You'll Need: Bachelors degree in Computer Science or equivalent experience 4 to 6 years of experience with a Strong background in MLOps, Python, GNU/Linux CLI Versatile and adaptable engineer who can address evolving needs of team. Strong understanding of data engineering principles and architecture Knowledge of relational database modelling and integration. Experience with NoSQL is helpful. Ability to manage cloud resources and technologies within AWS, including Sage maker, EC2, S3 Experience with software automation tools, e.g., Airflow, Ansible, Terraform, Jenkins Experience with automated unit testing and regression testing methodologies Familiar with Linux software build toolchains and patterns. (e.g., Make, gcc) Experience with source control and tracking (git) Strong teammate who enjoys working in a collaborative, fast-paced team-focused environment

Role & responsibilities Proven experience with MLOps practices and tools (Kubeflow, Kubernetes, LakeFS). Must have experience of the current AI landscape and its applications. Proficiency in Python and familiarity with containerization tools like Docker . Expertise on building Opensource Kubernetes from scratch and that too in an Air Gapped HSDN environment Excellent problem-solving skills and ability to work in a collaborative team environment. Preferred candidate profile Experience of 6 yrs and above. Expertise on building Opensource Kubernetes from scratch and that too in an Air Gapped HSDN environment Please share your updated resume at mantasha@bharatjobs.com along with below details: Total exp: Rel exp: C.CTC: E.CTC: NP: Current location: DOB:

We Advantum Health Pvt. Ltd - US Healthcare MNC looking for Senior AI/ML Engineer. We Advantum Health Private Limited is a leading RCM and Medical Coding company, operating since 2013. Our Head Office is located in Hyderabad, with branch operations in Chennai and Noida. We are proud to be a Great Place to Work certified organization and a recipient of the Telangana Best Employer Award. Our office spans 35,000 sq. ft. in Cyber Gateway, Hitech City, Hyderabad Job Title: Senior AI/ML Engineer Location: Hitech City, Hyderabad, India Work from office Ph: 9177078628, 7382307530, 9059683624 Address: Advantum Health Private Limited, Cyber gateway, Block C, 4th floor Hitech City, Hyderabad. Location: https://www.google.com/maps/place/Advantum+Health+India/@17.4469674,78.3747158,289m/data=!3m2!1e3!5s0x3bcb93e01f1bbe71:0x694a7f60f2062a1!4m6!3m5!1s0x3bcb930059ea66d1:0x5f2dcd85862cf8be!8m2!3d17.4467126!4d78.3767566!16s%2Fg%2F11whflplxg?entry=ttu&g_ep=EgoyMDI1MDMxNi4wIKXMDSoASAFQAw%3D%3D Job Summary: We are seeking an experienced and innovative AI Technical Lead to drive the design, development, and deployment of AI-powered solutions across our organization. You will be responsible for leading a team of machine learning engineers, data scientists, and software developers, while collaborating with cross-functional teams to build scalable and intelligent products. Your role will blend hands-on technical expertise with leadership and strategic thinking Key Responsibilities: Lead the end-to-end technical delivery of AI/ML projects, from data ingestion to model deployment. Design robust machine learning and deep learning models tailored to business needs. Collaborate with product managers, stakeholders, and engineering teams to identify opportunities for AI applications. Guide and mentor AI/ML engineers and developers; provide architectural and technical direction. Establish best practices for model training, validation, versioning, and monitoring. Ensure scalability, performance, and security of AI solutions in production environments. Stay up to date with the latest AI trends, tools, and research; apply innovations where appropriate. Review and approve technical design documents, code, and model performance metrics. Required Skills and Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. 5+ years of experience in software development, with at least 2+ years in leading AI/ML teams or projects. Strong proficiency in Python and frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience deploying models in production using platforms like AWS SageMaker, Azure ML, or Google Vertex AI. Solid understanding of data structures, algorithms, and software design principles. Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow). Excellent communication skills with the ability to articulate complex concepts to non-technical stakeholders. Preferred Qualifications: Experience with LLMs, generative AI, or computer vision. Background in big data technologies (e.g., Spark, Hadoop). Published research or contributions to open-source AI projects. Experience in regulated industries (e.g., healthcare, finance) is a plus. Follow us on LinkedIn, Facebook, Instagram, Youtube and Threads for all updates: Advantum Health Linkedin Page: https://www.linkedin.com/showcase/advantum-health-india/ Advantum Health Facebook Page: https://www.facebook.com/profile.php?id=61564435551477 Advantum Health Instagram Page: https://www.instagram.com/reel/DCXISlIO2os/?igsh=dHd3czVtc3Fyb2hk Advantum Health India Youtube link: https://youtube.com/@advantumhealthindia-rcmandcodi?si=265M1T2IF0gF-oF1 Advantum Health Threads link: https://www.threads.net/@advantum.health.india HR Dept, Advantum Health Pvt Ltd Cybergateway, Block C, Hitech City, Hyderabad Ph: 9177078628, 7382307530, 9059683624

Job Summary: AI Engineer Product Integration (LLMs & ML Systems) We are seeking a hands-on AI Engineer with proven experience in building, fine-tuning, and deploying Large Language Models (LLMs) and Machine Learning (ML) systems in production. This is not a research role were looking for someone who can turn models into scalable features, deeply integrated within our Optimiser CRM platform. Youll lead initiatives that turn AI into real value: automating workflows, enriching CRM data, and enhancing decision- making across our client base. This role requires strong engineering fundamentals, model fluency, and the ability to build reliable AI solutions in a multi-tenant environment. Key Responsibilities: AI/ML Development Design and fine-tune LLMs and ML models for specific CRM workflows. Build and optimize data pipelines for training, inference, and evaluation. Implement retrieval-augmented generation (RAG) and context injection strategies. Production Integration Package and deploy models into scalable production systems. Develop APIs and microservices for AI-powered features. Monitor model behavior in production; use telemetry to drive continuous improvement. Architecture & Compliance Ensure AI features adhere to multi-tenant data isolation and privacy standards. Collaborate with product and backend teams to align AI systems with Optimisers architecture. Implement access control, audit logging, and performance monitoring for AI services. Qualifications 2+ years of experience shipping ML/LLM features in a production environment. Strong Python development skills and hands-on experience with ML/LLM libraries (e.g., PyTorch, TensorFlow, LangChain, Hugging Face). Practical understanding of vector search, embeddings, and retrieval systems (e.g., Pinecone, FAISS, Weaviate). Experience deploying models as part of SaaS applications, especially in privacy-sensitive environments. Clear understanding of the ML lifecycle: from development to monitoring and iteration. Preferred (Not Mandatory) Exposure to prompt engineering and model evaluation techniques. Experience with fine-tuning LLMs or working with tools like LoRA, PEFT, or RAG pipelines. Familiarity with agent-based orchestration (e.g., LangChain agents, semantic routers). Understanding of MLOps (model versioning, deployment automation, rollback strategies). Location: Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Role & responsibilities Job Description: Lead Generative AI Engineer Overview We are seeking a highly skilled and experienced Generative AI Developer to lead our advanced AI solutions team. The ideal candidate will have a strong foundation in Generative AI, Machine learning, and Artificial intelligence, with a proven ability to develop cutting-edge AI solutions that transform business processes and drive innovation. The Lead GenAI Engineer will develop and deploy advanced Generative AI Products, including fine-tuning V/LLM models and implementing (Graph) RAG (Retrieval-Augmented Generation) solutions. This hands-on role requires deep technical expertise and as part of the GenAI team will implement and optimize Gen AI agents Responsibilities - Technical Leadership: Lead and mentor a team of AI developers, providing technical guidance and innovative problem-solving strategies. Drive multiple POC developments parallelly. - Solution Design/Development: Architect and develop advanced generative AI solutions, including large language models, multimodal AI systems, and complex generative workflows. Implement state-of-the-art GenAI & agents technologies and best practices. Develop, experiment with, and validate Gen AI applications aligning with business objectives. Model Development: Design, train, and optimize state-of-the-art generative AI models, including fine-tuning, prompt engineering, and model alignment techniques. Embed automated processes (LLMOps) Implement scalable, secure, and cost-effective Gen AI solutions to meet current and future business needs. Prototype and benchmark on the AI/ML stack, LLMOps, and AgentOps frameworks. Troubleshoot AI application issues, working closely with infrastructure teams and application owners. Foster innovation within the team to support a collaborative work environment. - Project Management: Oversee the entire project lifecycle from conceptualization through development, deployment, and continuous improvement. - Collaboration Identify opportunities to apply the latest advancements in Large Language Models (LLMs) and Agents Work with our cross-functional team to deliver features in an iterative manner Educate the organization both from IT and the business perspectives on Generative AI. - Research and Innovation: Stay at the forefront of generative AI advancements, exploring emerging technologies and implementing innovative AI solutions. - Performance Optimization: Develop strategies to improve model efficiency, reduce computational costs, and enhance AI system performance. - Ethical AI Implementation: Ensure responsible AI development, addressing bias, fairness, and ethical considerations in generative AI systems. - Client Engagement: Translate complex technical concepts into actionable insights for stakeholders and clients. Qualifications - Masters in computer science, Artificial Intelligence, Machine Learning, or a related field. - Minimum 6 years of experience in AI development, with a strong focus on generative AI technologies. 5+ years in at least 2 AI domains: NLP, NLG, Computer Vision, Machine Learning, etc. - Proven track record of leading and delivering successful AI development projects. - Expert-level proficiency in programming languages such as Python, with strong software engineering skills. - Deep expertise in machine learning frameworks and libraries (TensorFlow, PyTorch, Hugging Face). Key Technical Competencies - Generative AI Technologies: - Large Language Models (LLMs), Diffusion Models, Transformer Architectures, Multimodal AI Systems Extensive knowledge of LLM Python libraries: langchain, langGraph, promptflow, semantic kernel, Autogen, graphRag, promptflow Good software engineering background, (developing application, API, frontend integration, security best practices, experience with fastAPI, Asyncio). Distributed Computing, GPU Optimization, Containerization (Docker, Kubernetes) is a plus Strong experience with atleast 1 of Cloud AI Services (AWS, GCP, Azure) Preferably Azure Strong experience with Gen AI model deployment and monitoring (CI/CD, Weight & Biases GitHub pipelines is a plus). Advanced understanding of security, compliance, and ethical considerations in AI - Bias Detection and Mitigation, Responsible AI Principles, Model Interpretability, Ethical AI Frameworks - Advanced Machine Learning Techniques - Transfer Learning, Few-shot and Zero-shot Learning, Prompt Engineering, Model Fine-tuning Preferred Qualifications - Strong communication and collaboration abilities - Experience with cutting-edge generative AI research - Publications or contributions to open-source AI projects - Experience in domain-specific AI applications (healthcare, finance, insurance) - Demonstrated ability to explain complex AI concepts to non-technical stakeholders Additional Skills - Exceptional problem-solving and analytical thinking - Ability to work in fast-paced, innovative environments - Commitment to continuous learning and technological advancement Preferred candidate profile Please apply who are interested to work C2H/Contract role in large insurance company the candidate should come office at least 4 days Monthly work from office in Pune/Trivandrum

Role Overview: We are looking for a ML/AI Gen AI Expert with 4-7 years of experience for executing AI/GenAI use cases as POCs . Media domain experience (OTT, DTH, Web) is a plus. Key Responsibilities: Identify, define, and deliver AI/ML and GenAI use cases in collaboration with business and technical stakeholders. Design, develop, and deploy models (ML and GenAI) using Google Clouds Vertex AI platform. Fine-tune and evaluate LLMs for domain-specific applications, ensuring responsible AI practices. Collaborate with data engineers and architects to ensure robust, scalable, and secure data pipelines feeding ML models. Document solutions, workflows, and experiments to support reproducibility, transparency, and handover readiness. Core Skills: Strong foundation in machine learning and deep learning, including supervised, unsupervised, and reinforcement learning. Hands-on experience with Vertex AI, including AutoML, Pipelines, Model Registry, and Generative AI Studio. Experience with LLMs and GenAI workflows, including prompt engineering, tuning, and evaluation. Python and ML frameworks proficiency (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers). Strong collaboration and communication skills to work cross-functionally with data, product, and business teams. Technical Skills: Vertex AI on Google Cloud Model training, deployment, endpoint management, and MLOps tooling. GenAI tools and APIs Hands-on with PaLM, Gemini, or other large language models via Vertex AI or open source. Python Proficient in scripting ML pipelines, data preprocessing, and model evaluation. ML/GenAI Libraries scikit-learn, TensorFlow, PyTorch, Hugging Face, LangChain. Cloud & DevOps Experience with GCP services (BigQuery, Cloud Functions, Cloud Storage), CI/CD for ML, and containerization (Docker/Kubernetes) Experience in the media domain (OTT, DTH, Web) and handling large-scale media datasets. Immediate Joiners.

About the Role We are seeking a Generative AI Engineer with 69 years of experience who can independently explore, prototype, and present the art of the possible using LLMs, agentic frameworks, and emerging Gen AI techniques. This role combines deep technical hands-on development with non-technical influence and presentation skills. You will contribute to key Gen AI innovation initiatives, help define new protocols (like MCP and A2A) and deliver fully functional prototypes that push the boundaries of enterprise AI not just in Jupyter notebooks, but as real applications ready for production exploration. Key Responsibilities LLM Applications Agentic Frameworks Design and implement end-to-end LLM applications using OpenAI, Claude, Mistral, Gemini, or LLaMA on AWS, Databricks, Azure or GCP. Build intelligent, autonomous agents using LangGraph, AutoGen, LlamaIndex, Crew.ai, or custom frameworks. Develop Multi Model, Multi Agent, Retrieval-Augmented Generation (RAG) applications with secure context embedding and tracing with reports. Rapidly explore and showcase the art of the possible through functional, demonstrable POCs Advanced AI Experimentation Fine-tune LLMs and Small Language Models (SLMs) for domain-specific use. Create and leverage synthetic datasets to simulate edge cases and scale training. Evaluate agents using custom agent evaluation frameworks (success rates, latency, reliability) Evaluate emerging agent communication standards A2A (Agent-to-Agent) and MCP (Model Context Protocol) Business Alignment Cross-Team Collaboration Translate ambiguous requirements into structured, AI-enabled solutions. Clearly communicate and present ideas, outcomes, and system behaviors to technical and non-technical stakeholders Good-To-Have Microsoft Copilot Studio DevRev Codium Cursor Atlassian AI Databricks Mosaic AI Qualifications 6-9 years of experience in software development or AI/ML engineering At least 3 years working with LLMs, GenAI applications, or agentic frameworks. Proficient in AI/ML, MLOps concepts, Python, embeddings, prompt engineering, and model orchestration Proven track record of developing functional AI prototypes beyond notebooks. Strong presentation and storytelling skills to clearly convey GenAI concepts and value. Ability to independently drive AI experiments from Location: Location: Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Job Description If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere. Who we are: ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with datasolutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of theindustry and we want you to join us on our journey. ACVs network of brands includes ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services. ACV Auctions is opening its new India Development Center in Chennai, India, and were looking for talented individuals to join our team. As we expand our platform, were offering a wide range of exciting opportunities across various roles. At ACV, we put people first and believe in the principles of trust and transparency. If you are looking for an opportunity to work with the best minds in the industry and solve unique business and technology problems? Look no further! Join us in shaping the future of the automotive marketplace! At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs. What you will do: ACVs Machine Learning (ML) team is looking to grow its MLOps team. Multiple ACV operations and product teams rely on the ML teams solutions. Current deployments drive opportunities in the marketplace, in operations, and sales, to name a few. As ACV has experienced hyper growth over the past few years, the volume, variety, and velocity of these deployments has grown considerably. Thus, the training, deployment, and monitoring needs of the ML team has grown as weve gained traction. MLOps is a critical function to help ourselves continue to deliver value to our partners and our customers. Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of their stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable. The core responsibilities of this role are: Working with fellow machine learning engineers to build, automate, deploy, and monitor ML applications. Developing data pipelines that feed ML models. Deploy new ML models into production. Building REST APIs to serve ML models predictions. Monitoring performance of models in production. Required Qualifications: Graduate education in a computationally intensive domain or equivalent work experience. 5+ years of prior relevant work or lab experience in ML projects/research, and 1+ years as tech lead or major contributor on cross-team projects. Advanced proficiency with Python, SQL etc. Experience with cloud services (AWS / GCP) and kubernetes, docker, CI/CD. Preferred Qualifications: Experience with MLOps-specific tooling like Vertex AI, Ray, Feast, Kubeflow, or ClearML, etc. are a plus. Experience with EDA, including data pipeline building and data visualization. Experience with building ML models.