{"id":2548083,"url":"https://alion.io/job/job-mail-senior-data-scientist-ml-engineer","title":"Senior Data Scientist (ML Engineer)","company":{"id":701519,"name":"Job Mail","domain":"jobmail.co.za","url":"https://alion.io/company/job-mail","size_band":null,"is_staffing_agency":true,"employer_type":"agency","is_intermediary":true,"listed_via":"jobmail.co.za","ats_vendor":"Schema","truth_index":{"grade":"C","score":69,"open_postings":498,"ghost_share":0.436,"stale_share":0,"repost_share":0.659,"time_to_fill_p50_days":12,"computed_at":"2026-10-15T05:46:00Z"}},"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":["South 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API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"closed","first_seen_at":"2026-10-14T17:03:03Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T03:27:54Z","board_verified":false,"closed_at":"2026-10-15T03:27:54Z","days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"What you will be doing:\nDesign, prototype, build, deploy, and support production-grade Machine Learning, AI, and Generative AI solutions.\nProductionise and monitor Machine Learning models and pipelines using Databricks, including MLflow and Model Serving.\nDevelop and deploy AI agents, Generative AI solutions, and Retrieval-Augmented Generation (RAG) applications on Databricks.\nBuild reusable Machine Learning pipelines incorporating MLOps, CI/CD, automated testing, monitoring, and governance.\nDeploy and operate open-source AI/ML models on Azure Kubernetes Service (AKS).\nDevelop scalable APIs and microservices for AI/ML solutions using Docker and Kubernetes.\nMonitor model performance, drift, reliability, and overall operational health.\nPartner with Data Scientists to productionise models and translate data science solutions into reliable production services.\nCollaborate with platform engineering, cloud, security, and infrastructure teams to deliver scalable and secure AI/ML solutions.\nTroubleshoot and resolve technical issues across Machine Learning models, pipelines, platforms, and services.\nOptimise solutions for performance, scalability, cost, reliability, and operational efficiency.\nEstablish and promote engineering standards, frameworks, and best practices for AI/ML development and deployment.\nProvide technical guidance, coaching, and mentoring to other team members.\nStay current with emerging Machine Learning, AI, Generative AI, MLOps, and cloud technologies.\nContribute to the end-to-end delivery of AI/ML solutions, from experimentation and development through to production and ongoing support.\nWhat we are looking for:\nA relevant Degree in Computer Science, Engineering, Econometrics, Mathematical Statistics, Actuarial Science, Data Science, or a related field.\nMinimum 5 years’ experience in Machine Learning Engineering, AI Engineering, Data Science, or a closely related field.\nStrong hands-on experience developing, deploying, and supporting Machine Learning and AI solutions in production environments.\nExperience with MLOps, DevOps, software engineering practices, CI/CD, and infrastructure automation.\nStrong programming skills in Python and SQL, with experience developing and consuming REST APIs.\nHands-on experience with Databricks, MLflow, Model Serving, and cloud-based AI/ML platforms.\nExperience with Azure Kubernetes Service (AKS), Kubernetes, and Docker.\nStrong understanding of Machine Learning model deployment, monitoring, model drift, observability, and production operations.\nExperience with Apache Spark and distributed computing.\nPractical experience with Large Language Models (LLMs), Generative AI, RAG, and AI agents/agentic AI.\nExperience working closely with Data Scientists to operationalise and productionise Machine Learning models.\nAbility to design scalable, reliable, secure, and maintainable AI/ML solutions.\nStrong problem-solving skills and the ability to troubleshoot complex technical issues.\nAbility to communicate complex technical concepts effectively to both technical and business stakeholders.\nExperience within financial services, banking, or another regulated environment would be advantageous.\nPreferred Certifications:\nMicrosoft Azure certifications such as AZ-104, AZ-305, or AI-102.\nDatabricks certifications in Data Engineering, Machine Learning Engineering, or Generative AI Engineering.\nCKA or CKAD Kubernetes certifications.\nRelevant DevOps, MLOps, or Platform Engineering certifications.\nRecognised Machine Learning, Artificial Intelligence, or Data Science certifications.\nAWS or Google Cloud certifications would be advantageous.\nPlease note that if you do not hear from us within 3 weeks, consider your application unsuccessful.Please note that most of our positions are remote; however, candidates should reside within travelling distance of the client site, as the working arrangements may change depending on business requirements.","description_format":"text","description_chars":3926,"description_truncated":false,"requirements":{"experience_years_min":5,"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 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