Senior Engineer, AI & Machine Learning
India-Remote
- Pay
- Pay not listed
- Work setting
Remote stated — work setting source
Listed location: India-Remote
Read the full posting- Employment
Full-time — employment source
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingDevelop and implement end-to-end AI/ML models and workflows in Palantir Foundry and AIP
Lead development and production deployment of scalable ML models
Build end-to-end data pipelines for large-scale datasets
Use Palantir AIP features such as Agent Studio and RAG workflows to ground models in data
Mentor junior engineers and help shape team processes
From the employer’s posting
Develop and implement end-to-end AI/ML models and workflows within the Palantir Foundry and AIP environment
Lead the development and deployment of scalable and efficient ML models in production environments.
Build end-to-end data pipelines for collecting, processing, and analyzing large-scale datasets.
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.
Mentor junior engineers and contribute to the development of team processes and best practices.
Education & alternatives
What you’ll need (Required) - 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.
Tools in this posting
- Java
- Python
- AWS
- Docker
- Hadoop
- Kafka
- Kubernetes
- MLflow
- Spark
- Airflow
- Keras
- PyTorch
- scikit-learn
- TensorFlow
- C++
Source — Tool mentions in context
- 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.
- Experience with deep learning techniques (e.g., CNNs, RNNs, GANs, etc.). - Familiarity with MLOps and tools for model deployment and monitoring (e.g., MLflow, Kubeflow, Docker, Kubernetes). - Knowledge of data engineering practices and tools like Apache Kafka, Airflow, etc.
- 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.
- Familiarity with MLOps and tools for model deployment and monitoring (e.g., MLflow, Kubeflow, Docker, Kubernetes). - Knowledge of data engineering practices and tools like Apache Kafka, Airflow, etc.
- 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.
Posting record
Report an errorOpen 6 monthsWe first saw this listing 192 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 15, 2026 · 192 days ago
- Recorded sightings
- 343
- Last seen by us
- Oct 24, 2026
- Employer says posted
- Dec 16, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on edwards.wd5.myworkdayjobs.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
Innovation starts from the heart. At Edwards Lifesciences, we’re dedicated to developing ground-breaking technologies with a genuine impact on patients’ lives. At the core of this commitment is our investment in cutting-edge information technology. This supports our innovation and collaboration on a global scale, enabling our diverse teams to optimize both efficiency and success. As part of our IT team, your expertise and commitment will help facilitate our patient-focused mission by developing and enhancing technological solutions.
AI Factory team focuses in developing and delivering cutting edge technologies to improve patient care. Our vision is to provide proactive care and smart recovery to our patient community who are fighting cardiovascular disease through innovative connected solutions.
In this role you will be working alongside Product Engineering Leads in developing various desktop, web and mobile software fueled by a robust AI engine that will improve patient care. We look for candidates who are not only technically competent but can share the same pride we feel for the work we do to serve our patient community.
How you will make an impact:
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.
What you’ll need (Required)
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.
What else we look for (Preferred)
Preferred certifications include Foundry Data Engineer Certification, Foundry Solution Architect Certification, or Foundry Application Developer Certification..
Experience with deep learning techniques (e.g., CNNs, RNNs, GANs, etc.).
Familiarity with MLOps and tools for model deployment and monitoring (e.g., MLflow, Kubeflow, Docker, Kubernetes).
Knowledge of data engineering practices and tools like Apache Kafka, Airflow, etc.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
India-Remote
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
See how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.