{"id":179969,"url":"https://alion.io/job/metafusion-mlops-engineer","title":"MLOps Engineer","company":{"id":11707,"name":"Metafusion","domain":"metafusion.ai","url":"https://alion.io/company/metafusion","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":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ahmedabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":10000,"max_usd":25000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"C++","optional":false},{"name":"CI/CD","optional":false},{"name":"Computer Vision","optional":false},{"name":"Docker","optional":false},{"name":"FAISS","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"NLP","optional":false},{"name":"Pinecone","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Ray Serve","optional":false},{"name":"TensorRT","optional":false},{"name":"Terraform","optional":false},{"name":"Triton Inference Server","optional":false},{"name":"vLLM","optional":false},{"name":"Weaviate","optional":false}],"status":"live","first_seen_at":"2026-08-31T12:58:08Z","employer_posted_date":null,"last_verified_at":"2026-08-31T12:58:08Z","board_verified":false,"closed_at":null,"days_open":47,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":47},"description":"We are looking for a talented and driven MLOps Engineer to join our AI/ML team. In this role, you will design and build scalable ML infrastructure, MLOps pipelines, and CI/CD workflows for deploying and managing NLP, generative AI, and computer vision models.\nResponsibilities:\nML Infrastructure and Platform: Design, build, and maintain scalable MLOps pipelines and infrastructure for training, deploying, and managing NLP, GenAI, and computer vision models.\nCI/CD for Machine Learning: Implement automated continuous integration and continuous deployment (CI/CD) pipelines for ML models, ensuring smooth transitions from development to production environments.\nModel Serving and Deployment: Lead the deployment and lifecycle management of Large Language Models (LLMs), Vision-Language Models (VLMs), and other ML models using scalable serving engines (e. g., vLLM, Triton Inference Server, Ray Serve).\nMonitoring and Observability: Set up comprehensive monitoring frameworks to track model performance, data drift, resource utilization, and system health in real-time production environments.\nPipeline Orchestration: Develop and manage end-to-end ML workflows encompassing data ingestion, preprocessing, training, evaluation, and inference using tools like Kubeflow, MLflow, or Apache Airflow.\nCloud and Resource Optimization: Optimize cloud infrastructure (AWS/GCP/Azure) for cost, latency, and throughput. Ensure efficient hardware resource allocation across GPUs and distributed computing clusters.\nCross-Functional Collaboration: Collaborate closely with data scientists, NLP/CV engineers, and software engineers to define hardware constraints, capacity planning, and deployment strategies.\nRequirements:\nQualification: BTech in CS/AI/Data Science or related discipline.\nPossess 2-5 years of professional experience in MLOps, machine learning engineering, or closely related technical domains.\nDemonstrated expertise in the deployment and lifecycle management of Large Language Models (LLMs), VLMs, and diverse ML architectures within production-grade environments.\nHigh proficiency with MLOps and serving frameworks, including MLflow, Kubeflow, vLLM, Triton Inference Server, and TensorRT for high-performance inference.\nPractical experience implementing vector databases (such as Pinecone, FAISS, or Weaviate) alongside robust CI/CD tooling like GitHub Actions, Jenkins, or Terraform.\nAdvanced coding skills in Python, C++, and Bash, with a strong background in managing containerized workloads using Docker and Kubernetes across major cloud platforms (AWS, GCP, or Azure).\nComprehensive understanding of ML pipelines and observability, including model versioning, registries, and monitoring frameworks like Prometheus and Grafana for tracking system health and data drift.\nExcellent communication abilities with a collaborative mindset and a focus on solving complex technical challenges.","description_format":"text","description_chars":2897,"description_truncated":false,"requirements":{"experience_years_min":2,"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":["Natural Language Processing","Computer Vision","AI Search"],"lifecycle":[{"event":"open","at":"2026-08-31T13:44:08Z"}],"visa":[],"liveness":{"score":4,"band":"cold","label":"Long shot","p_open":0.4,"p_active":0.381,"p_room":0.28,"age_days":46,"expected_fill_days":19,"reasons":["seen:46","win:tail","crowd:junior"],"computed_at":"2026-10-17T05:46:00Z"},"pay":null,"html_url":"https://alion.io/job/metafusion-mlops-engineer","json_url":"https://alion.io/job/metafusion-mlops-engineer.json","meta":{"generated_at":"2026-10-18T12:45:41Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":18876,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-19T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":11707},"rest":"https://alion.io/mcp/rest/get_company?id=11707"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmetafusion-mlops-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fmetafusion-mlops-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fmetafusion-mlops-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/metafusion-mlops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmetafusion-mlops-engineer"}]}