{"id":1506801,"url":"https://alion.io/job/live-connections-mlops-engineer","title":"MLOps Engineer","company":{"id":3800101,"name":"Live Connections","domain":"livecjobs.com","url":"https://alion.io/company/live-connections","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":47000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":29},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"TensorFlow","optional":false},{"name":"AI Agents","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"MLFlow","optional":true},{"name":"NLP","optional":true},{"name":"Semantic Search","optional":true},{"name":"Semantic Search","optional":true}],"status":"live","first_seen_at":"2026-09-30T05:12:06Z","employer_posted_date":null,"last_verified_at":"2026-09-30T05:12:06Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"MLOps Engineer\n\nLocation : Bangalore - Whitefield\n\nExperience : 7 - 10 Years\n\nEmployment Type : Full-time\n\nRole Overview : \n\nWe are looking for an experienced MLOps Engineer with strong expertise in machine learning engineering, cloud-based ML platforms, and AI/ML model deployment. The ideal candidate will be responsible for building scalable ML pipelines, automating model development and deployment workflows, and enabling reliable productionisation of AI/ML and Generative AI solutions.\n\nTech Stack : \n\n- Python, MLOps, Deep Learning, RAG & LLMs, TensorFlow, Databricks\n\nKey Responsibilities : \n\n- Design, build and maintain scalable MLOps pipelines for model development, training, validation and deployment.\n\n- Develop and automate CI/CD workflows for machine learning models and AI applications.\n\n- Deploy, monitor and maintain ML models in production environments.\n\n- Work closely with Data Scientists, ML Engineers, Data Engineers and application teams to productionise machine learning solutions.\n\n- Develop and optimise machine learning workflows using Python and TensorFlow.\n\n- Build and manage data and ML pipelines using Databricks and related technologies.\n\n- Support the development and deployment of Deep Learning models.\n\n- Work on Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and other Generative AI use cases.\n\n- Design pipelines for data preparation, feature engineering, model training and inference.\n\n- Implement model versioning, experiment tracking, model validation and lifecycle management.\n\n- Establish monitoring mechanisms for model performance, data quality, drift and system health.\n\n- Optimise ML infrastructure for scalability, reliability and cost efficiency.\n\n- Troubleshoot production issues and continuously improve the reliability of ML systems.\n\n- Ensure security, governance and best practices are followed throughout the ML lifecycle.\n\n- Stay updated with emerging technologies and best practices across MLOps, GenAI and AI engineering.\n\nRequired Skills : \n\n- 7 - 12 years of overall experience in MLOps / ML Engineering / AI Engineering.\n\n- Strong hands-on programming experience in Python.\n\n- Strong understanding of MLOps principles and ML lifecycle management.\n\n- Hands-on experience with TensorFlow and Deep Learning frameworks.\n\n- Experience working with LLMs and Generative AI.\n\n- Practical understanding of RAG architectures, embeddings, vector search and retrieval pipelines.\n\n- Strong experience with Databricks and ML/data processing workflows.\n\n- Experience building and managing automated ML pipelines.\n\n- Good understanding of model deployment, monitoring and productionisation.\n\n- Experience with CI/CD, version control and automated deployment practices.\n\n- Strong understanding of data pipelines and data engineering concepts.\n\nGood to Have : \n\n- Experience with cloud platforms such as AWS, Azure or GCP.\n\n- Experience with Docker and Kubernetes.\n\n- Knowledge of MLflow or similar experiment/model lifecycle management tools.\n\n- Experience with vector databases and semantic search.\n\n- Exposure to Agentic AI and AI application development.\n\n- Knowledge of infrastructure-as-code and cloud-native architectures.\n\n- Experience implementing responsible AI, security and governance practices.\n\nKey Competencies : \n\n- Strong problem-solving and analytical skills.\n\n- Ability to work effectively with cross-functional teams.\n\n- Strong communication and stakeholder-management skills.\n\n- Ability to translate AI/ML requirements into scalable production solutions.\n\n- Strong ownership and focus on building reliable, production-ready systems.\n\nSkills\nMLOps, Python, Tensorflow, Databricks, Machine Learning, Deep Learning, NLP, Generative AI, Artificial Intelligence, RAG, LLM","description_format":"text","description_chars":3752,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":[],"lifecycle":[{"event":"open","at":"2026-09-30T06:02:59Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":24,"reasons":["seen:1","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/live-connections-mlops-engineer","json_url":"https://alion.io/job/live-connections-mlops-engineer.json","meta":{"generated_at":"2026-10-02T03:05:42Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4273,"day_limit":5000,"remaining_today":727,"minute_limit":60,"resets_at":"2026-10-03T00:00:00Z"}}}