{"id":1759394,"url":"https://alion.io/job/n-ix-senior-aiml-engineer","title":"Senior AI/ML Engineer","company":{"id":13248,"name":"N-iX","domain":"n-ix.com","url":"https://alion.io/company/n-ix","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":75,"open_postings":15,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-05T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ukraine"],"countries":["UA"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":40000,"max_usd":99000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1757},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"NLP","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"XGBoost","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-10-02T12:07:07Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-06T00:16:08Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"We are looking for a Senior AI/ML Engineer to design, develop, and enhance AI-driven solutions within the Palantir Foundry and AIP ecosystem.\nIn this role, you will take ownership of developing production-ready machine learning and LLM-based solutions, from understanding business needs and exploring data to designing technical approaches, implementing solutions, and integrating them into Foundry workflows. You will work closely with data engineers, business analysts, and domain experts, contribute to technical decisions, and help establish best practices for building scalable and reliable AI solutions.\nKey Responsibilities:\nDesign and develop AI/ML solutions for predictive analytics, classification, forecasting, automation, and AI-assisted workflows within Palantir Foundry, leveraging Python, Ontology objects, pipelines, and workflows.\nDesign, implement, evaluate, and optimize LLM/NLP and RAG solutions using Palantir AIP, including prompt engineering, embeddings, retrieval strategies, vector search, and text processing.\nOwn the end-to-end lifecycle of AI solutions, from experimentation and model development to deployment, monitoring, and continuous improvement.\nCollaborate with data engineers to understand data sources, ensure data quality, and design efficient and scalable data processing approaches.\nIntegrate AI solutions into production workflows and optimize them for accuracy, reliability, latency, scalability, and cost-efficiency.\nContribute to technical architecture and design decisions, including model, framework, and tool selection; proactively identify technical risks, improvement opportunities and proactively propose solutions.\nWork with business and domain stakeholders to translate business needs into practical, scalable, and production-ready AI solutions, clearly communicating technical decisions and model limitations.\nIdentify technical risks, limitations, and opportunities for improvement and proactively propose solutions.\nRequirements:\n4+ years of experience in machine learning, AI engineering, applied data science, or related fields.\nStrong Python skills and hands-on experience with ML frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch.\nStrong practical experience with LLMs, NLP, or GenAI applications, including prompt engineering, embeddings, text processing, summarization, or similar use cases.\nSolid hands-on experience designing and implementing RAG architectures, vector databases, and retrieval strategies.\nStrong understanding of the ML lifecycle, including data preparation, feature engineering, model development, evaluation, deployment, and monitoring.\nExperience working with both structured and unstructured data, including tabular data, time series, text, and documents.\nAbility to independently analyze ambiguous problems, propose technical approaches, and drive solutions from concept to implementation.\nStrong communication skills, with the ability to explain AI concepts, technical decisions, and model behavior to non-technical stakeholders.\nUpper-Intermediate English or higher.\nNice to Have:\nProficiency in Foundry Ontology, Object Builders, and Code Repositories.\nExperience in big pharma or highly regulated industries.\nKnowledge of data privacy, compliance, and security best practices in AI applications.\nFamiliarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)\nWe offer*:\nFlexible working format - 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