{"id":1252084,"url":"https://alion.io/job/funic-tech-private-limited-mlops-engineer-ai-deployment","title":"MLOps Engineer - AI Deployment","company":{"id":3800661,"name":"FUNIC TECH PRIVATE LIMITED","domain":"funictech.com","url":"https://alion.io/company/funic-tech-private-limited","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Schema","truth_index":{"grade":"D","score":40,"open_postings":13,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-09-30T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","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":21000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":22},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Chroma","optional":false},{"name":"CUDA","optional":false},{"name":"CUDA Toolkit","optional":false},{"name":"Databricks","optional":false},{"name":"FAISS","optional":false},{"name":"Grafana","optional":false},{"name":"Hugging Face","optional":false},{"name":"Jenkins","optional":false},{"name":"Keycloak","optional":false},{"name":"Kubernetes","optional":false},{"name":"Langfuse","optional":false},{"name":"LLMOps","optional":false},{"name":"Milvus","optional":false},{"name":"MLFlow","optional":false},{"name":"MySQL","optional":false},{"name":"OpenShift","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Pinecone","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Ray Serve","optional":false},{"name":"Rest API","optional":false},{"name":"SGLang","optional":false},{"name":"Splunk","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Triton Inference Server","optional":false},{"name":"vLLM","optional":false},{"name":"WebSockets","optional":false},{"name":"Ray","optional":true}],"status":"live","first_seen_at":"2026-09-16T04:53:30Z","employer_posted_date":null,"last_verified_at":"2026-09-16T04:53:30Z","board_verified":false,"closed_at":null,"days_open":14,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":14},"description":"About the Role:\n\nWe are looking for a hands-on MLOps Engineer specializing in ML engineering, model deployment, model governance, and observability. The role covers the complete lifecycle of Deep Learning models, LLMs, and SLMs.\n\nKey Responsibilities:\n\n- Build and manage MLOps and LLMOps pipelines.\n\n- Deploy, host, and scale Deep Learning models, LLMs, and SLMs.\n\n- Manage model versioning, deployment, rollout, rollback, and retirement.\n\n- Host models on Databricks, Kubernetes, OpenShift, and GPU infrastructure.\n\n- Implement model governance, lineage, approval workflows, and compliance controls.\n\n- Build monitoring, tracing, logging, and drift-detection capabilities.\n\n- Optimize model latency, throughput, GPU utilization, and cost.\n\n- Support cloud, on-premises, hybrid, and air-gapped environments.\n\nRequired Skills:\n\n- 3 - 5 years in MLOps, LLMOps, ML Engineering, or AI Engineering.\n\n- Strong Python.\n\n- Hands-on Databricks and/or Azure ML.\n\n- Experience with Deep Learning, LLMs, SLMs, RAG, and Hugging Face.\n\n- Experience deploying PyTorch and TensorFlow models.\n\n- Strong Kubernetes, Databricks, and GPU deployment experience.\n\n- Experience with vLLM, Triton Inference Server, Ray Serve, SGLang, or Databricks Model Serving.\n\n- Strong NVIDIA GPU and CUDA knowledge.\n\n- Model Registry, Governance, Monitoring, Drift Detection, and AI Observability.\n\n- SQL Server, PostgreSQL, Oracle, MySQL, or MongoDB.\n\n- Vector databases such as Pinecone, Chroma, FAISS, Milvus, or Azure AI Search.\n\n- REST APIs, WebSockets, and Streaming HTTP.\n\n- MLflow, OpenTelemetry, LangFuse, Splunk, and Grafana/ELK.\n\n- Jenkins and Azure DevOps.\n\n- Keycloak/authentication setup experience.\n\nSkills\nMLOps, Python, Kubernetes, Databricks, Deep Learning, PyTorch, Tensorflow, Grafana, Artificial Intelligence","description_format":"text","description_chars":1794,"description_truncated":false,"requirements":{"experience_years_min":3,"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":["Artificial Intelligence","Commerce","Design & Creative","Web Design"],"lifecycle":[{"event":"open","at":"2026-09-25T18:04:06Z"}],"liveness":{"score":34,"band":"fade","label":"Fading","p_open":0.85,"p_active":0.529,"p_room":0.75,"age_days":14,"expected_fill_days":17,"reasons":["seen:14","stale_co","velocity","win:late"],"computed_at":"2026-09-30T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/funic-tech-private-limited-mlops-engineer-ai-deployment","json_url":"https://alion.io/job/funic-tech-private-limited-mlops-engineer-ai-deployment.json","meta":{"generated_at":"2026-10-01T01:45:01Z","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":1263,"day_limit":5000,"remaining_today":3737,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}