{"id":160180,"url":"https://alion.io/job/faktion-generative-ai-engineer","title":"Generative AI Engineer","company":{"id":54451,"name":"Faktion","domain":"faktion.com","url":"https://alion.io/company/faktion","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"D","score":52,"open_postings":15,"ghost_share":0.8,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Antwerp, Belgium"],"countries":["BE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Copilot","optional":false},{"name":"Data Augmentation","optional":false},{"name":"Docker","optional":false},{"name":"FastAPI","optional":false},{"name":"LangChain","optional":false},{"name":"Langfuse","optional":false},{"name":"Machine Learning","optional":false},{"name":"RAG","optional":false},{"name":"Agile","optional":true},{"name":"Azure","optional":true},{"name":"GitHub","optional":true},{"name":"Python","optional":true},{"name":"Scrum","optional":true}],"status":"live","first_seen_at":"2024-03-27T18:22:41Z","employer_posted_date":"2024-03-27","last_verified_at":"2026-10-17T18:21:03Z","board_verified":true,"closed_at":null,"days_open":934,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":933},"description":"As a Generative AI Engineer you specialize in integrating generative AI solutions and applying generative models. Your work enables advancements in various industries for our customers, including data augmentation, RAG systems, virtual assistants, and more, expanding the AI capabilities and driving innovation in applications that require realistic outputs. We are hiring a highly motivated Generative AI Engineer to join our talented engineering team. As a Generative AI Engineer, you will be responsible for developing and implementing cutting-edge generative AI models to solve complex problems and drive innovation for our customers. You will work closely with data scientists, software engineers, and product managers to design, build, and deploy AI-powered solutions that enhance the business of our customers.\nSome key responsibilities:\nImplementing and augmenting generative AI models and tools such as GPT, LLama, langchain, Langfuse..\n\nImplementing and augmenting existing third-party solutions (eg. Microsoft Copilot, etc.) with proprietary solutions and methods to ensure the customer has the best possible integration of generative AI capabilities in his workforce\n\nCollaborating with cross-functional teams to define AI project requirements and objectives, ensuring alignment with overall business goals.\n\nConducting research to stay up-to-date with the latest advancements in generative AI, machine learning, and deep learning techniques and identify opportunities to integrate them into our products and services.\n\nOptimizing existing generative AI models for improved performance, scalability, and efficiency.\n\nDeveloping and maintaining MLOPS pipelines, including data preprocessing, feature extraction, model training, and evaluation.\n\nDeveloping and maintaining containerized AI back-ends using tools like Docker and FastAPI.\n\nDeveloping clear and concise documentation, including technical specifications, user guides, and presentations, to communicate complex AI concepts to both technical and non-technical stakeholders.\n\nContributing to the best practices and standards for generative AI development within the organization.\n\nProviding technical mentorship and guidance to other team members on the topic of generative AI\n\nRequirements\nExcellent written and verbal communication skills in native Dutch and English (French is a plus).\n\nYou have a degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A Ph.D. is a plus.\n\nYou have solid experience with implementing generative AI models, with a strong understanding of deep learning techniques like transformer models.\n\nYou are proficient in Python and have experience with machine-learning libraries.\n\nYou have a strong knowledge of data structures, algorithms, and software engineering principles.\n\nYou are familiar with cloud-based platforms and services, such as Azure.\n\nYou know software development methodologies, such as Agile or Scrum.\n\nYou possess excellent problem-solving skills and can think critically and creatively to develop innovative AI solutions.\n\nYou have strong communication skills and can effectively convey complex technical concepts to a diverse audience.\n\nYou possess a proactive mindset and can work independently and collaboratively in a fast-paced, dynamic environment.\n\nFollowing experiences are a plus:\nShowing your passion through GitHub repos or prior engagements in Kaggle competitions\n\nProven track record of developing and deploying scalable machine learning models.\n\nPublications in relevant AI/ML conferences and journals.\n\nExperience in one of our focus domains: Data Quality, Retail, Manufacturing, Finance\n\nWe offer:\nA rewarding salary package that includes additional perks like a company car and fuel card or a mobility budget, comprehensive hospitalization, group insurance, and a top-tier laptop and smartphone.\n\nBenefit from a company culture that stimulates both individual and team development, fostering professional growth.\n\nParticipate in team-building activities and gatherings, a great opportunity to unwind and engage with our vibrant team initiatives.\n\nA flexible hybrid working policy to choose where, how, and when you want to work.\n\nAt Faktion we build AI, and we use it thoughtfully in our own processes too. During your application, AI tools may help us with practical steps, like checking that your documents came through complete. They never decide who moves forward: every application is read by a real person on our team, and every decision is made by a human. Curious how this works, or how your data is handled? 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