Architect designing enterprise - grade AI/ML architectures for Quantiphi. Leading AI applications and ML strategy with a focus on scalability, security, and integration.
About the role
- Senior Engineer developing AI/ML solutions to enhance patient care at Edwards Lifesciences. Collaborating with cross-functional teams to deliver impactful technologies in healthcare.
Responsibilities
- 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.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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