Job Description
Job Description:
Required Skills & Experience:
- 10+ years of experience in Data Science, Machine Learning, Artificial Intelligence, and Advanced Analytics.
- Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- Proven track record of delivering impactful AI/ML solutions, research initiatives, and enterprise-scale data science projects.
- Strong expertise in Deep Learning, Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs).
- Hands-on experience in setting up AI/GenAI infrastructure, model deployment, MLOps, and scalable AI platforms.
- Extensive experience with Prompt Engineering, LLM fine-tuning, Retrieval-Augmented Generation (RAG), vector databases, and AI agents.
- Strong programming skills in Python and/or Java.
- Proficiency with machine learning and deep learning frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, and related AI ecosystems.
- Experience designing and implementing end-to-end AI solutions, from data ingestion and model development to production deployment.
- Expertise in data engineering, feature engineering, model optimization, and performance monitoring.
- Strong knowledge of cloud platforms such as AWS, Azure, or GCP for AI/ML workloads.
- Experience working with structured and unstructured data at enterprise scale.
- Excellent analytical, problem-solving, and communication skills.
- Ability to collaborate effectively with cross-functional teams, stakeholders, and business leaders.
Top Skill (Must Have):
- Extensive hands-on experience with Palantir Foundry
- Building data pipelines and workflows
- Ontology development and data modeling
- AI/ML solution deployment within Foundry
- Data integration, transformation, and operational analytics
- Foundry Workshop, Code Repositories, and Machine Learning applications
Preferred Qualifications:
- Publications, patents, or significant contributions in AI, Deep Learning, NLP, or Generative AI.
- Experience with knowledge graphs, vector databases, and enterprise AI platforms.
- Experience leading AI initiatives and mentoring junior data scientists.
- Familiarity with MLOps tools, CI/CD pipelines, and model governance frameworks.