{"id":2041322,"url":"https://alion.io/job/hcltech-platform-engineer-iii-7","title":"Platform Engineer III","company":{"id":225,"name":"HCLTech","domain":"hcltech.com","url":"https://alion.io/company/hcltech","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":11000,"max_usd":27000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":19},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Argo Workflows","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Feast","optional":false},{"name":"Feature Store","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Grafana","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Terraform","optional":false},{"name":"Vertex AI","optional":false}],"status":"live","first_seen_at":"2026-10-07T17:59:39Z","employer_posted_date":"2026-10-07","last_verified_at":"2026-10-13T05:49:19Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Job Summary\nWe are looking for an MLOps Engineer to design, build, and operate scalable infrastructure and pipelines for deploying and managing machine learning models in production. The role bridges Data Science, Machine Learning Engineering, DevOps, and Cloud Engineering, ensuring models can move reliably from experimentation to production with strong automation, monitoring, governance, and reproducibility.\nKey Responsibilities\nDesign and implement end-to-end MLOps pipelines covering model training, validation, deployment, monitoring, and retraining.\nBuild automated CI/CD/CT pipelines for machine learning applications.\nDeploy and manage ML models as scalable batch, real-time, or streaming services.\nContainerize ML applications using Docker and orchestrate workloads using Kubernetes.\nBuild and maintain cloud-based ML infrastructure on AWS, Azure, or GCP.\nImplement experiment tracking, model versioning, model registries, and artifact management.\nEstablish monitoring for model performance, data drift, concept drift, latency, infrastructure health, and failures.\nAutomate infrastructure provisioning using Infrastructure as Code tools such as Terraform.\nWork closely with Data Scientists to productionize models and improve reproducibility of ML experiments.\nCollaborate with DevOps, Data Engineering, Security, and application teams to integrate ML solutions into enterprise platforms.\nImplement security, access control, auditability, and governance practices across the ML lifecycle.\nTroubleshoot production ML pipelines and continuously improve platform reliability, scalability, and cost efficiency.\nDevelop reusable MLOps frameworks, templates, and engineering standards.\nSkill Requirements\nStrong programming skills in Python and scripting experience with Bash/Shell.\nHands-on experience with Docker and Kubernetes.\nExperience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform.\nExperience building CI/CD pipelines using tools such as Jenkins, GitHub Actions, GitLab CI/CD, or Azure DevOps.\nHands-on experience with MLOps tools/platforms such as MLflow, Kubeflow, Azure Machine Learning, AWS SageMaker, or Vertex AI.\nGood understanding of the machine learning lifecycle, including training, validation, deployment, inference, monitoring, and retraining.\nExperience with Git and software engineering best practices.\nKnowledge of Infrastructure as Code using Terraform, CloudFormation, or equivalent technologies.\nExperience with monitoring and observability platforms such as Prometheus, Grafana, ELK, or cloud-native monitoring services.\nUnderstanding of REST APIs, microservices, and distributed systems.\nFamiliarity with data pipelines, databases, object storage, and feature engineering workflows.\nOther Requirements\nExperience with orchestration platforms such as Apache Airflow, Kubeflow Pipelines, or Argo Workflows.\nKnowledge of feature stores such as Feast or cloud-native feature-store solutions.\nExperience implementing automated model/data drift detection and retraining workflows.\nExposure to Generative AI/LLMOps, including LLM deployment, evaluation, prompt/version management, vector databases, and RAG pipelines.\nUnderstanding of GPU-based workloads and distributed model training/inference.\nKnowledge of enterprise security, compliance, and responsible AI practices.","description_format":"text","description_chars":3340,"description_truncated":false,"requirements":{"experience_years_min":null,"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":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Systems Integrators"],"lifecycle":[{"event":"open","at":"2026-10-07T17:59:39Z"}],"visa":[],"liveness":{"score":98,"band":"hot","label":"Hiring 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