{"id":3239366,"url":"https://alion.io/job/knowdis-ai-devops-ml-engineer","title":"DevOps / ML Engineer","company":{"id":4675,"name":"KnowDis AI","domain":"knowdis.ai","url":"https://alion.io/company/knowdis-ai","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":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"DVC","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubeflow","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-25T14:35:00Z","employer_posted_date":null,"last_verified_at":"2026-10-25T14:35:00Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"We're looking for a DevOps / ML Engineer who sits at the crossroads of infrastructure, backend development, and machine learning operations. You won't be building ML models from scratch, but you'll need a solid understanding of ML algorithms and pipelines to design, deploy, and maintain the systems that power them. Think of this as an MLOps-flavored backend role: you'll build CI/CD pipelines, debug ML pipeline failures, propose automation solutions, and keep our production ML systems running smoothly.\n\nResponsibilities: \nDesign, build, and continuously improve CI/CD pipelines for both traditional backend services and ML workloads.\nDebug and resolve issues across ML pipelines from data ingestion to model serving, working closely with the data science team.\nDevelop and maintain Python-based backend services and tooling that support our ML infrastructure.\nPropose and implement MLOps automation solutions: model versioning, experiment tracking, automated retraining, and monitoring.\nManage cloud infrastructure (AWS/GCP/Azure), container orchestration (Docker, Kubernetes), and IaC tools (Terraform, Pulumi).\nMonitor production systems, set up alerting, and ensure high availability of ML-powered features.\nCollaborate with data scientists and backend engineers in an agile environment to ship reliable, scalable systems.\n\nRequirements: \n2-3+ years of experience in DevOps, backend engineering, or MLOps roles.\nStrong Python skills: You can write production-grade backend code, not just scripts.\nSolid understanding of ML algorithms and workflows (training, evaluation, and deployment) enough to debug pipeline issues and have informed conversations with data scientists.\nHands-on experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar).\nExperience with containerization (Docker) and orchestration (Kubernetes).\nFamiliarity with ML tooling: MLflow, Kubeflow, Airflow, DVC, or equivalent.\nA proactive, ownership-driven mindset: you identify bottlenecks and propose solutions before being asked.\nComfort with agile workflows and fast iteration cycles: You thrive in environments where priorities shift and quality still matters.\nBachelor's / Master's Degree in CS / ECE / EE / AI / ML / Data Science.\nSkills\nci/cd, devops, github 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