Machine learning Engineer

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Machine learning Engineer

Sia

Location

Maastricht, , Netherlands

Experience

Mid

Posted

Jul 7, 2026

Apply by

August 6, 2026

Applicants

0

Early applicantFull-timeHybrid

Job Description

## Company Description Sia is a next-generation, global management consulting group born digital, augmented by data, enhanced by creativity, and driven by responsibility. We partner with clients to resolve challenges and capitalize on opportunities. We believe that in today’s world of change and disruption, optimism is a force multiplier. ## Job Description **What you will do** As an expert in the field of Machine Learning Engineering you will be responsible for the growth of our Data team, both professionally as well as in size. You will be in charge of shaping and executing the future of your expertise within Sia. You will work on client projects as well as on building our own Sia AI solutions, together with our Dutch team of Data Scientists, our French Data Engineering team, and other business units of Sia Global. Your responsibilities include: - Leading an internal team towards the development of AI products; - Working in a multidisciplinary team on client projects as an expert on your subject; - Making architectural and design decisions for cloud environments; - Building production level ML/AI solutions with solid software engineering; - Guiding Data Scientists to scale up their models into production (parallelizing, optimizing, tuning, testing, and wrapping); - Giving trainings, leading internal meetings and organizing external events; - Participating in team meetings and workshops with clients; - Writing blog articles, presenting at conferences and sending out press releases on the subject that you lead. **Who you will work with** The Data Science team is young, diverse and growing (10+). You will join a team that will challenge you and invest in your professional development. We have a flat structure and rely on the entrepreneurial spirit of our members: initiative is highly encouraged. We are striving for well-being, diversity and knowledge-sharing inside the team, so that we can grow together. **Who you are** - You are an established technical professional that wants to make the next step in their career, taking on more leadership responsibilities. - You have first-rate project management and time management skills. - You are a true problem solver, you turn complex issues into simple and impactful business solutions. - You are enthusiastic for applying Data Science/Engineering solutions to business problems. - You have excellent communication skills and can present complicated concepts in a synthetic way. - You have the ability to adapt rapidly and work on a range of different business areas within a challenging environment. - You have the ability to work collaboratively in a team environment. **In return, you can expect:** - An international company that gives importance to diversity, inclusion, employee well-being and corporate social responsibilities actions. - A great working atmosphere with friendly and professional colleagues where innovation and entrepreneurship are encouraged - A personal development plan with a regular follow-up as well training opportunities to develop yourself - A competitive salary with great advantages, like mobility budget, hospital insurance, performance -related bonus,... ## Qualifications - MSc level education in Computer Science, Applied Mathematics, Artificial Intelligence, Embedded Systems or related field of study. - 2-4 years of experience in building production-quality ML/Deep Learning pipelines and models. - Good understanding of Machine Learning fundamentals and strong knowledge in a specific domain (e.g., Computer Vision, Deep Learning, NLP). - Expert coding skills in Python and at least one of these languages: Scala, C++, Java. - Hands-on experience with database management languages (e.g., SQL, PostgreSQL). - Hands-on experience in cloud-based infrastructures (AWS/GCP/Azure). - Hands-on experience with Unix-based command line and DevOps tools (Git, Docker, Kubernetes). - Hands-on experience with big data technologies (e.g. Spark, Hadoop, Databricks). - You have a strong interest in data and AI-related topics, the ability to quickly build expertise in these areas, and you’re excited about helping our clients seize the opportunities they offer. - Experience with coaching/mentoring other engineers. - Prior experience in Management Consulting is a strong plus. - Willingness to travel and work at local and international clients. - Fluency in spoken and written English and Dutch is required. ## Additional Information We are unable to provide a work permit for this position Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.  Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

Key Responsibilities

  • Lead internal team towards development of AI products
  • Work in multidisciplinary teams on client projects
  • Make architectural and design decisions for cloud environments
  • Build production-level ML/AI solutions with solid software engineering
  • Guide Data Scientists to scale up models into production
  • Provide training and lead internal meetings
  • Participate in team meetings and workshops with clients
  • Write blog articles and present at conferences

Requirements

  • MSc level education in Computer Science
  • Applied Mathematics
  • Artificial Intelligence
  • Embedded Systems or related field of study

Skills Required

PythonScalaC++JavaSQLPostgreSQLAWSGCPAzureGitDockerKubernetesSparkHadoopDatabricksMachine LearningDeep LearningComputer VisionNLPProject managementTime managementProblem solvingCommunicationAdaptabilityCollaborationLeadershipMentoring

Benefits

  • Mobility budget
  • Hospital insurance
  • Performance-related bonus
  • Personal development plan
  • Training opportunities
  • Diversity and inclusion focus
  • Employee well-being

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