{"id":1138693,"url":"https://alion.io/job/cloudfactory-mlops-support-engineer","title":"MLOps Support Engineer","company":{"id":48012,"name":"CloudFactory","domain":"cloudfactory.com","url":"https://alion.io/company/cloudfactory","size_band":"51-200","is_staffing_agency":false,"is_intermediary":false,"ats_vendor":"Workable","truth_index":{"grade":"B","score":80,"open_postings":5,"ghost_share":0,"stale_share":0.8,"repost_share":0,"time_to_fill_p50_days":30,"computed_at":"2026-09-23T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"hiring_geo_confidence":"structured","locations":["Kathmandu, Nepal"],"countries":["NP"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":95000,"max_usd":250000,"period":"year","method":"role_country_seniority_unknown","sample_n":10},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Incident Management","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"A/B Testing","optional":true},{"name":"Databricks","optional":true},{"name":"Grafana","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLM","optional":true},{"name":"Machine Learning","optional":true},{"name":"MLFlow","optional":true},{"name":"New Relic","optional":true},{"name":"Power BI","optional":true},{"name":"Prompt Engineering","optional":true}],"status":"live","first_seen_at":"2026-09-23T09:32:40Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-09-23T12:42:58Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"At CloudFactory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world. By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale.\nMore than just a workplace, we’re a global community founded on strong relationships and the belief that meaningful work transforms lives. Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following.\nOur Culture\nAt CloudFactory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:\nMission-Driven: We focus on creating economic and social impact.\nPeople-Centric: We care deeply about our team’s growth, well-being, and sense of belonging.\nInnovative: We embrace change and find better ways to do things together.\nGlobally Connected: We foster collaboration between diverse cultures and perspectives.\nIf you’re passionate about innovation, collaboration, and making a real impact, we’d love to have you on board!\nAbout the role:\nThe MLOps Support Engineer is an operations-first role, focused on ensuring AI/ML systems remain stable, observable, and supportable in production environments. This is not a data science or feature development role.\nThe primary objective is to maintain continuous performance of ML models and associated pipelines with minimal disruption to both internal and client-facing services. You will provide Tier 1 and Tier 2 support, escalating to Tier 3 Engineering as needed.\nWhat you’ll do:\nProvide Tier 1 / Tier 2 operational support for AI/ML solutions.\nIdentify failed jobs, degraded pipelines, or performance anomalies.\nTriage incidents, investigate issues, and coordinate escalation to Tier 3 Engineering.\nParticipate in on-call rotas once established.\nValidate that pipelines and jobs complete successfully.\nMonitor data pipeline health, model execution, and basic performance metrics.\nIdentify operational issues before they impact customers\nRespond or alert customers when there has been an outage or issue with one of their models.\nSupport incident management, rollback, and recovery activities.\nUse and maintain runbooks and operational documentation.\nWork with Engineering to improve supportability and observability.\nContribute to knowledge sharing to reduce single points of failure.\nWork within defined SLAs and support processes as the service matures\nBuild quarterly business reviews to provide updates on the health of the ML Models.\nEvaluate champion/challenger models to see if a new model should be promoted.\nMonitor for model drift and performance degradation, while validating that updates (new champion models or added data) do not introduce bias.\nRequirements\nEssential\nExperience in operations, DevOps, SRE, or platform support roles.\nStrong troubleshooting skills in production environments.\nProficiency in SQL and scripting (Python, Bash) for developing and automating ML workflows.\nFamiliarity with Cloud-hosted systems (AWS, GCP, Azure) for cloud-based ML services.\nGit: Solid understanding of version control, particularly in collaborative development environments.\nComfortable working from runbooks and structured processes.\nDesirable\nExposure to AI/ML systems in production.\nFamiliarity with monitoring and observability tools (Grafana, PowerBI, New Relic).\nKnowledge of MLOps tooling and data platforms (ML FLow, Databricks)\nExperience supporting customer-facing platforms.\nKnowledge of containerization (Kubernetes) is a plus.\nExperience of LLM Prompt Engineering and troubleshooting\nEarly career in MLOps or ML Engineering.\nSomeone who is eager to learn about complex predictive models.\nBackground in computer science, informatics, or related fields\nPassion for Machine Learning and AI: An eager learner who is excited about working with cutting-edge ML technologies and is passionate about optimizing and maintaining ML models in production environments.\nEarly Career in MLOps or ML Engineering: Ideally, Junior ML Engineer with a strong desire to grow in the field of MLOps and AI operations.\nA Collaborative Mindset: You thrive in a team setting and are ready to contribute to model improvement, A/B testing, and iterative development.\nAttention to Detail: A focus on model performance, bias prevention, and ensuring optimal model behavior as new data and models are introduced.\nAdditional information:\nNepal\nThis role provides MLOps coverage from 07:45 - 16:45* NPT for US-based customers.You will be required to work on a shift rota to cover 8 hour time blocks during this time period and potentially outside of them if a model has issues.\nRotational On-Call work will also be required.\nColombia\nThis role provides MLOps coverage from 9am to 9pm* Colombia. You will be required to work on a shift rota to cover 8 hour time blocks during this time period and potentially outside of them if a model has issues.\nRotational On-Call work will also be required.\n*note that these hours are subject to change upon review.\nBenefits\nAt CloudFactory, we believe that work should be more than just a job, it should be a platform for growth, impact, and community. Here, you’ll earn with purpose, learn every day, and serve a mission that truly matters. If you're looking for a career where you can develop professionally, contribute meaningfully, and be part of a global movement, we’d love to have you on this journey!\nJoin us today and be part of our mission to connect people and technology for a better world! Apply now and bring your whole, authentic self to work, we can’t wait to meet you!","description_format":"text","description_chars":5699,"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":["Data Entry & Processing","Business Process Outsourcing (BPO)","AI Training Data & Annotation"],"lifecycle":[{"event":"open","at":"2026-09-23T09:32:40Z"}],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":30,"reasons":["conf:0","win:early"],"computed_at":"2026-09-23T13:08:49Z"},"pay":null,"html_url":"https://alion.io/job/cloudfactory-mlops-support-engineer","json_url":"https://alion.io/job/cloudfactory-mlops-support-engineer.json","meta":{"generated_at":"2026-09-23T13:08:49Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers"}}