Participate in agile development processes, including sprint planning and daily stand-ups
Collaborate with cross-functional teams (data scientists, software engineers, product managers, business leads) to define requirements and deliver high-quality ML solutions.
Develop and implement end-to-end AI/ML models and workflows within the Palantir Foundry and AIP environment
Leverage Palantir AIP features, such as Agent Studio, RAG (retrieval-augmented generation) workflows, and copilots, to ground models in relevant data sources and the Ontology.
Conduct research on open-source tools and ML techniques relevant to the medical domain
Design, implement, and optimize advanced machine learning algorithms to solve complex business problems.
Lead the development and deployment of scalable and efficient ML models in production environments.
Drive research and experimentation to explore new ML techniques, tools, and frameworks.
Build end-to-end data pipelines for collecting, processing, and analyzing large-scale datasets.
Mentor junior engineers and contribute to the development of team processes and best practices.
Stay up-to-date with the latest trends and advancements in machine learning and AI.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or related field (PhD is a plus).
5+ years of professional experience in machine learning engineering, with a strong focus on deploying machine learning models in production environments.
1+ years of hands on experience with Palantir Foundry ecosystem and AIP
Proficiency in programming languages such as Python, Java, C++, or similar.
Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Keras, etc.).
Strong understanding of machine learning algorithms, statistics, and data structures.
Experience with cloud platforms such as AWS for model deployment and data storage.
Familiarity with big data technologies like Hadoop, Spark, or similar tools is a plus.
Solid experience with version control systems (Git) and agile development methodologies.
Strong communication skills and the ability to work effectively in cross-functional teams.
Tech Stack
AWS
Cloud
Hadoop
Java
Keras
Python
PyTorch
Scikit-Learn
Spark
Tensorflow
Benefits
Health insurance
Retirement plans
Paid time off
Flexible work arrangements
Professional development
Senior Engineer, AI & Machine Learning at Edwards Lifesciences | JobVerse