Senior AI/ML Engineer

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. We deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software,IoT, and more to global industry leaders and Fortune 500 companies. Join us to create technology that drives real change for businesses and people across the world.

We are looking for a Senior AI/ML Engineer to design, build, and scale AI-driven solutions within the Palantir Foundry and AIP ecosystem.

In this role, you will take ownership of developing production-ready AI systems, including LLM-powered applications, RAG pipelines, and machine learning models, while collaborating closely with cross-functional teams. You will contribute to architectural decisions, ensure high-quality implementations, and help evolve AI capabilities within enterprise environments.
 

Responsibilities:

• Design, develop, and enhance AI-driven solutions, including machine learning models, LLM-based applications, and NLP workflows for analytics, automation, and decision-making
• Build and optimize RAG pipelines, including embeddings, retrieval strategies, chunking approaches, and hybrid search techniques
• Develop AI solutions within Palantir Foundry, leveraging Ontology objects, pipelines, and workflows
• Apply LLMs and GenAI techniques (prompt engineering, fine-tuning, embeddings, retrieval-augmented generation) using Palantir AIP
• Own the end-to-end lifecycle of AI solutions: data preparation, model development, evaluation, deployment, and monitoring
• Collaborate with data engineers to ensure data quality, pipeline efficiency, and scalable data processing
• Integrate AI models into production workflows to deliver business-facing insights and automation capabilities
• Evaluate and improve model and system performance, including accuracy, latency, scalability, and cost-efficiency
• Contribute to architecture decisions, including selection of tools, frameworks, and design patterns for AI systems
• Implement and follow MLOps / LLMOps best practices, including versioning, evaluation frameworks, monitoring, and continuous improvement
• Ensure responsible AI practices, including data privacy, governance, and compliance considerations
• Collaborate with stakeholders to translate business needs into practical and scalable AI solutions
• Mentor junior engineers and contribute to knowledge sharing within the team
   

Requirements:

• 4–5+ years of experience in AI/ML engineering, applied data science, or related fields
• Strong proficiency in Python and experience with ML frameworks (e.g., scikit-learn, XGBoost, PyTorch, TensorFlow)
• Hands-on experience with LLMs, NLP, or GenAI applications (prompt engineering, embeddings, text processing, summarization, etc.)
• Practical experience with RAG architectures, vector databases, and retrieval strategies
• Strong understanding of the ML lifecycle: data preparation, feature engineering, model training, evaluation, and deployment
• Experience building and deploying production-grade AI systems
• Familiarity with structured and unstructured data processing (tabular, time series, text, documents)
• Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
• Understanding of MLOps / LLMOps practices, including monitoring, evaluation, and iteration
• Experience working in enterprise data environments with cross-functional teams
• Ability to communicate AI concepts and results to technical and non-technical stakeholders
• Upper-Intermediate English or higher
   

Nice to Have:

• Experience with Palantir Foundry (Ontology, Object Builders, Code Repositories, AIP)
• Experience in regulated industries (e.g., pharma, finance)
• Experience with distributed data processing (e.g., Spark)
• Exposure to multilingual or multimodal AI systems

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers