{"id":2512304,"url":"https://alion.io/job/t-mapp-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":4420641,"name":"T-mapp","domain":"t-mapp.com","url":"https://alion.io/company/t-mapp","size_band":"1001-5000","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"unspecified","remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":110000,"max_usd":244000,"period":"year","method":"global_role_seniority_cell","sample_n":1986},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-10-14T09:11:44Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-14T19:57:36Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nSenior Machine Learning Engineer\nOur client is a global data intelligence company that transforms large-scale real-world data into reliable, actionable insights for high-impact use cases. The organization operates at the intersection of data engineering, machine learning, and modern AI systems, enabling data-driven decision-making at scale.\nThe company is currently at a key stage of technological evolution, focused on scaling production-grade machine learning systems, incorporating modern AI and agentic architectures, and strengthening the reliability, automation, and observability of its data platforms, with direct impact on product and business outcomes.\nWhat will you do in this role?\nAs a Senior Machine Learning Engineer, you will take on a hands-on, senior technical role with strong ownership.\nYour mission will be to design, build, and operate production Machine Learning systems, working with large-scale geospatial datasets and ensuring that models, pipelines, and agentic workflows run in a reliable, scalable, and automated manner.\nWe are counting on your expertise to:\nDesign, build, and maintain large-scale geospatial data pipelines capable of processing millions or billions of records.\nBuild, deploy, and monitor ML/AI models in production (batch) with a strong focus on quality, performance, and reliability.\nImplement and integrate agent-based systems into real operational workflows.\nDevelop backend services and ML tooling that enable other teams to consume models and data products efficiently.\nEstablish end-to-end observability for pipelines, models, and agents, including metrics, alerting, and tracing.\nOptimize distributed systems while balancing performance, cost, and scalability.\nCollaborate closely with product and business teams, translating real-world needs into technical solutions that drive measurable value.\nWhat should you bring to the role?\nAdvanced English, both speaking and writing.\nProven experience as a senior Machine Learning Engineer, with production ML systems running at scale.\nStrong background in distributed data processing using tools such as Spark, Python, and Scala.\nHands-on experience designing and operating end-to-end ML systems (data ingestion, training, deployment, monitoring).\nSolid experience working with cloud infrastructure, particularly across data, compute, and ML services.\nPractical knowledge of CI/CD pipelines, infrastructure as code, and containerization.\nAbility to work autonomously with a high level of technical judgment and ownership.\nExperience collaborating effectively with both technical and non-technical stakeholders in remote, cross-functional environments.\nDesired competencies\nStrong engineering mindset, focused on building robust systems rather than isolated models.\nStructured thinking and ability to solve complex, ambiguous problems.\nHigh analytical capability and sound technical decision-making.\nStrong focus on reliability, scalability, and long-term maintainability.\nClear and effective communication with diverse stakeholders.\nProactive attitude and strong sense of responsibility for the systems you build and operate.\nWhat will you gain from this role?\nA high-impact senior technical role with real ownership over critical machine learning systems.\nThe opportunity to work with massive datasets and modern AI technologies in production environments.\nDirect exposure to product and business teams, with tangible impact on outcomes.\nAn international, remote-first environment with highly skilled technical peers.\nThe opportunity to continue building a strong, long-term technical career in large-scale Machine Learning and data systems.\nSubmit your resume and join a process that can change your life.\nBest regards,\nT-mapp Team","description_format":"text","description_chars":3749,"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":[{"language":"English","level":"Advanced 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