MLOps Engineer
4 weeks ago
Job Description - MLOps Engineer (46 Years)We are seeking an experienced MLOps Engineer with strong expertise in LLM deployment, optimization, and scalable model serving. The ideal candidate will work at the intersection of AI/ML engineering, DevOps, and cloud infrastructure, ensuring seamless integration of large-scale AI models into production.Responsibilities :- Design, deploy, and manage Large Language Models (LLMs) in production environments.- Build and optimize scalable ML pipelines for training, fine-tuning, and inference.- Implement MLOps best practices including CI/CD for ML, experiment tracking, and automated retraining workflows.- Optimize model performance through quantization, pruning, distillation, and GPU/TPU acceleration.- Manage and monitor LLM serving infrastructure with Kubernetes, Docker, and orchestration tools.- Collaborate with data scientists and researchers to integrate models into real-world applications.- Ensure reliability, scalability, and security of deployed ML systems.- Implement observability and monitoring for model performance, drift detection, and resource utilization.Key Skills & Experience :- 4-6 years of hands-on experience in MLOps / ML Engineering.- Expertise in LLM deployment, fine-tuning, and inference optimization.- Strong knowledge of Kubernetes, Docker, MLflow, Kubeflow, Airflow, or similar platforms.- Experience with model compression, distributed training (Horovod, DeepSpeed, Ray), and serving frameworks (TensorRT, Triton Inference Server, TorchServe, Hugging Face Inference).- Proficiency in Python, PyTorch/TensorFlow, and cloud platforms (AWS/GCP/Azure).- Hands-on experience with CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI).- Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus) for LLM applications.- Understanding of observability tools (Prometheus, Grafana, ELK, Datadog).Preferred :- Experience with retrieval-augmented generation (RAG) pipelines.- Knowledge of LangChain, LlamaIndex, or similar frameworks.- Exposure to multi-modal LLMs and real-time inference systems. (ref:hirist.tech)
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MLOps Engineer
3 days ago
New Delhi, India Meril Full timeMLOps Engineer | Nuvo AI / Meril Life Sciences (Vapi, Gujarat)We’re looking for a passionate and skilled MLOps Engineer to join our AI & Machine Learning Division at Meril Life Sciences, where innovation meets healthcare.If you’re excited about designing scalable machine learning pipelines, automating model deployments, and ensuring reliable ML systems...
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MLOps Engineer
4 weeks ago
New Delhi, India Meril Full timeMLOps Engineer | Nuvo AI / Meril Life Sciences (Vapi, Gujarat)We’re looking for a passionate and skilled MLOps Engineer to join our AI & Machine Learning Division at Meril Life Sciences, where innovation meets healthcare.If you’re excited about designing scalable machine learning pipelines, automating model deployments, and ensuring reliable ML systems...
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MLOps Engineer
3 weeks ago
New Delhi, India Persistent Systems Full timeAbout Position:We are hiring a skilled MLOps Engineer to build and manage robust ML pipelines that support scalable, secure, and automated deployment of machine learning models. This role is critical in enabling seamless collaboration between data science, engineering, and DevOps teams for enterprise-grade AI/ML adoption.Role: MLOps Engineer Location: All...
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Senior MLOps Engineer
4 days ago
Delhi, India Atomic North Full timeHiring: MLOps EngineerExperience: 5–8 Years (with at least 2+ years in MLOps or ML deployment roles)Location: Bengaluru, Bhopal, Gurgaon, Hyderabad, Jaipur, Mumbai, Pune , ChennaiAbout the RoleWe are seeking a skilled MLOps Engineer to operationalize and scale machine learning solutions on AWS. The ideal candidate will have strong expertise in cloud...
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MLOps Engineer
1 week ago
Delhi, India Capgemini Full timeResponsibilitiesExperience in developing MLOps framework cutting ML lifecycle: model development, training, evaluation, deployment, monitoring including Model GovernanceExpert in Azure Databricks, Azure ML, Unity CatalogHands-on experience with Azure DevOps, MLOPS CI/CD Pipelines, Python, Git, DockerExperience in developing standards and practices for MLOPS...
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MLOps Engineer
1 week ago
New Delhi, India Yotta Data Services Private Limited Full timeAbout the Role:We’re looking for a strategic Senior MLOps Engineer to lead the end-to-end design, implementation, and scaling of our AI infrastructure. You’ll partner with researchers, product teams, and DevOps to turn prototypes into production services that meet strict SLAs for latency, reliability, and cost efficiency.Responsibilities:• Core MLOps...
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MLOps Engineer
7 days ago
New Delhi, India Yotta Data Services Private Limited Full timeAbout the Role: We’re looking for a strategic Senior MLOps Engineer to lead the end-to-end design, implementation, and scaling of our AI infrastructure. You’ll partner with researchers, product teams, and DevOps to turn prototypes into production services that meet strict SLAs for latency, reliability, and cost efficiency.Responsibilities: •Core MLOps...
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MLOps Engineer
3 days ago
New Delhi, India Yotta Data Services Private Limited Full timeAbout the Role:We're looking for a strategic Senior MLOps Engineer to lead the end-to-end design, implementation, and scaling of our AI infrastructure. You'll partner with researchers, product teams, and DevOps to turn prototypes into production services that meet strict SLAs for latency, reliability, and cost efficiency.Responsibilities:• Core MLOps...
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Senior MLOps Engineer
3 days ago
New Delhi, India Atomic North Full timeHiring: MLOps Engineer Experience:5–8 Years (with at least 2+ years in MLOps or ML deployment roles) Location:Bengaluru, Bhopal, Gurgaon, Hyderabad, Jaipur, Mumbai, Pune , ChennaiAbout the Role We are seeking askilled MLOps Engineerto operationalize and scale machine learning solutions on AWS. The ideal candidate will have strong expertise in cloud...
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MLOps Engineer
2 days ago
Delhi, NCR, India Zorba Consulting Full time ₹ 8,00,000 - ₹ 12,00,000 per yearKey Responsibilities : Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. Implement monitoring and...
