{"id":3271254,"url":"https://alion.io/job/xtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector","title":"Senior ML/AI Engineer - AWS, Databricks & MLOps (Public Sector)","company":{"id":3414,"name":"Xtremax","domain":"xtremax.com","url":"https://alion.io/company/xtremax-pte-ltd","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":89,"open_postings":47,"ghost_share":0,"stale_share":0.255,"repost_share":0,"time_to_fill_p50_days":60,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"contractor","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Singapore"],"countries":["SG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":60000,"max_usd":131000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"AIOps","optional":false},{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon ECS","optional":false},{"name":"Amazon EKS","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Glue","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Grafana","optional":false},{"name":"IAM","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Prometheus","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-10-26T11:48:05Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T00:06:17Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"At Xtremax, we're looking for a Senior ML/AI Engineer to help build the engineering foundations that make machine learning and AI systems reliable in production. Working across AWS and Databricks, you'll help turn experiments and notebooks into maintainable services, reusable pipelines and operational AI capabilities.\nYou'll work across the ML lifecycle, from data preparation and feature engineering through experiment tracking, deployment, monitoring, evaluation, retraining and retirement. Using technologies such as Python, PySpark, SQL, Databricks and MLflow, you'll improve the reliability, reproducibility and cost efficiency of AI workloads while establishing reusable engineering patterns for the wider team.\nThis is a hands-on engineering role that spans software, data and infrastructure. You'll collaborate with data scientists, data engineers, platform engineers, product teams and governance stakeholders to build secure and observable services, improve deployment practices, and support the continued maturity of MLOps and AIOps capabilities.\nResponsibilities\nDesign and implement reusable MLOps/AIOps components for experiment tracking, model registry, workflow orchestration, deployment, monitoring, feedback and retraining.\nProductionise notebooks and prototypes into tested, modular and containerised batch jobs, APIs, model-serving endpoints and AI services.\nBuild reliable data and feature engineering pipelines on Databricks and AWS for structured and unstructured data.\nOptimise Spark and SQL workloads, partitioning, file layouts, cluster configuration and scheduling to improve performance and cloud cost efficiency.\nAutomate testing and promotion of code, data, features, prompts, models and infrastructure through CI/CD and continuous-training workflows.\nImplement versioning, lineage, evaluation evidence, approval records, rollback and retirement mechanisms for ML/AI workloads.\nBuild system and model monitoring, dashboards, alerts and operational runbooks, and support incident diagnosis and root-cause analysis.\nDevelop repeatable model evaluation and regression-testing practices, including champion-challenger comparisons and A/B testing where appropriate.\nApply cloud security and responsible-AI controls covering access, encryption, secrets, audit logging and safeguards for untrusted AI inputs.\nSupport model maintenance, retraining, data ingestion, experimentation and performance reporting for recommendation and search workloads.\nImprove reusable engineering patterns, operational reliability and MLOps maturity, while documenting solutions and transferring knowledge to internal teams.\nRequirements\nDegree or diploma in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems or a related technical discipline.\nTypically 4-7 years of relevant software, data or ML engineering experience, including delivery and operation of ML/AI systems beyond prototype stage.\nStrong Python software engineering skills, including API development, packaging, automated testing, Git and modular design.\nHands-on experience with Databricks and MLflow for experiment tracking, model registry, orchestration or model serving.\nStrong experience with Spark/PySpark and SQL, including distributed processing, query optimisation and pipeline troubleshooting.\nExperience building lakehouse or data-lake pipelines using Databricks, Delta Lake and AWS S3, including layered data patterns.\nExperience with data modelling, data contracts, metadata, lineage, quality validation and reconciliation.\nExperience with workflow orchestration using Databricks Workflows, AWS Glue, Step Functions, EventBridge, Airflow or equivalent tools.\nPractical AWS data and cloud engineering experience across relevant services, such as S3, Glue, IAM, KMS, Lambda, ECR, ECS/EKS, CloudWatch or Redshift.\nExperience with Docker, infrastructure as code such as Terraform, and CI/CD tools such as GitLab CI, GitHub Actions, Jenkins or Harness.\nUnderstanding of the ML lifecycle, including data validation, feature engineering, evaluation, deployment, monitoring, drift, retraining and retirement.\nExperience with observability, operational troubleshooting, reproducibility and traceability.\nWorking knowledge of cloud security, access management, encryption, secrets management and audit logging.\nPreferred\nExperience with Unity Catalog, Delta Live Tables, Lakeflow or feature stores.\nExperience with streaming, change data capture or governed data sharing.\nExperience productionising generative AI or agentic systems, including orchestration, evaluation and guardrails.\nFamiliarity with Kubernetes, OpenTelemetry, Prometheus, Grafana or model drift tooling.\nExperience with A/B testing or champion-challenger deployment.\nExperience supporting high-volume or low-latency AI services.\nFamiliarity with Singapore public-sector technology environments, security controls and responsible-AI governance.\nBenefits\nBy submitting your resume/CV, you consent and agree to allow the information provided to be used and processed by or on behalf of Xtremax Pte Ltd for purposes related to your registration of interest in current or future employment with us and for the processing of your application for employment.\nYou also represent to us that you have obtained the consent of your referees when you disclose to us their personal data for the purpose of conducting reference checks.\nThe personal data held by us relating to your application will be kept strictly confidential and in accordance with the PDPA. You may also refer to our Privacy Policy for more details here:\nWe regret to inform you that should you not consent to providing the necessary data required for us to process your application, your application will be considered void.","description_format":"text","description_chars":5770,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Government","IT Consulting & Digital Transformation","Managed IT Services (MSP)","Custom Software Development"],"lifecycle":[{"event":"open","at":"2026-10-26T11:48:05Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":4,"expected_fill_days":60,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-10-31T05:58:55Z"},"pay":null,"html_url":"https://alion.io/job/xtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector","json_url":"https://alion.io/job/xtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector.json","meta":{"generated_at":"2026-11-01T01:40:49Z","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":2477,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-02T00:00:00Z"}},"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":3414},"rest":"https://alion.io/mcp/rest/get_company?id=3414"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fxtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector"},{"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%2Fxtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector"},{"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%2Fxtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector"},{"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/xtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fxtremax-senior-mlai-engineer-aws-databricks-mlops-public-sector"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3271254}},{"tool":"search_jobs","arguments":{"company":"xtremax.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3271254},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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