{"id":96171,"url":"https://alion.io/job/devapo-data-5","title":"DATA","company":{"id":1439,"name":"Devapo","domain":"devapo.io","url":"https://alion.io/company/devapo","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Traffit","truth_index":{"grade":"D","score":40,"open_postings":20,"ghost_share":1,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-17T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":16000,"max":23000,"currency":"PLN","period":"month","gross":null,"usd_annual":70620},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Agentic Workflows","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Bedrock","optional":false},{"name":"Azure","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"OpenAI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Vertex AI","optional":false},{"name":"Databricks","optional":true},{"name":"Multi-Agent Systems","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-03-12T13:14:20Z","employer_posted_date":"2026-03-12","last_verified_at":"2026-10-17T11:52:21Z","board_verified":true,"closed_at":null,"days_open":219,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":218},"description":"Data Scientist with AI (B2B)\nWe are looking for an experienced Data Scientist with AI to drive innovation by designing, developing, and deploying enterprise-grade Machine Learning and Generative AI solutions for our clients.\nAbout Devapo\nAt Devapo, we focus on continuous self-development and acquiring new knowledge. If you are a fast learner, want to participate in international projects, are a team player, and can work independently - join us!\nWe provide our clients with more than just code - we want to equip them with tools that allow their businesses to flourish. Our clients’ success is our success, which is why we ensure that everyone who creates Devapo has a long-term goal in mind.\nKey Responsibilities:\nLead end-to-end projects in traditional Data Science, Machine Learning, and cutting-edge Generative AI and Large Language Models (LLMs) - from research and experimentation to production deployment.\n\nDesign and implement scalable AI/ML pipelines and MLOps practices using cloud-native services (e.g., Azure Machine Learning, GCP Vertex AI, AWS SageMaker).\n\nDevelop, optimize, and evaluate LLM-based applications, including RAG (Retrieval-Augmented Generation) systems, leveraging vector stores and prompt orchestration.\n\nCollaborate with Data Engineers and BI teams to ensure access to high-quality, well-structured data for model training and inference.\n\nApply advanced statistical analysis, experimentation (A/B testing, causal inference), and modeling techniques to solve complex business problems.\n\nContribute to defining AI roadmaps, ensuring solutions align with business objectives, and driving measurable impact (e.g., cost reduction, performance optimization).\n\nEnsure adherence to AI governance, security, and data compliance standards within regulated environments.\n\nResearch and evaluate new AI frameworks (e.g., LangChain, CrewAI) and technologies (e.g., multi-modal AI, agentic workflows).\n\nRequirements:\nMinimum 4+ years of experience in Data Science or a similar role, with at least 1+ year of hands-on experience in Generative AI/LLMs.\n\nStrong programming proficiency in Python (including libraries like PyTorch, TensorFlow, or scikit-learn).\n\nHands-on experience with one or more major cloud AI platforms: Azure OpenAI, GCP Vertex AI, or AWS Bedrock/SageMaker.\n\nDeep understanding of LLMs, embeddings, vector databases, and RAG architectures.\n\nProficiency in SQL and experience working with large, complex datasets in cloud environments.\n\nSolid foundation in statistics, probability, and experimental design (A/B testing).\n\nFamiliarity with containerization (Docker) and orchestration (Kubernetes/MLOps tools) for deploying models at scale.\n\nExcellent communication skills in English (minimum B2 level) and the ability to effectively collaborate with technical and business stakeholders.\n\nNice to Have:\nExperience with multi-agent systems, behavior trees, or reinforcement learning.\n\nBackground in regulated industries (e.g., finance, insurance, healthcare).\n\nExperience with Databricks or Apache Spark ecosystem.\n\nWhat We Offer:\nSalary: 16 000 - 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