Job VC
Senior AI/ML Engineer
Technologies
Description
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.
Key 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
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.
Key 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