Machine Learning Engineer - Natural Language Processing (NLP)

Key Skills

Deep Learning, Docker, HuggingFace, Java Programming, Kubernetes-K8s, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Python Programming, PyTorch

Job Description

A World-Changing Company

Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more.

The Role

Our Machine Learning team develops state of the art deep learning models to address immediate customer needs and to ensure Palantir’s platforms offer unparalleled machine learning capabilities.

We are looking for someone that is passionate about ML systems of natural language processing (NLP) and deep learning to lead the design and implementation of ML infrastructure to train and serve deep learning models. In this role, you will build innovative NLP products that facilitate an enhanced user experience in operational workflows. You will work with ML researchers on the latest deep learning models to build solutions in areas of information retrieval (IR), question answering, document summarization, entity, event and relationship extraction and classification, as well as structured text extraction from documents.

Core Responsibilities

• Architect performant, efficient, secure and scalable systems to tune, serve and evaluate large language models
• Drive implementation, testing, releases and monitoring for data processing pipelines and ML products
• Work closely with machine learning researchers to align model development with business needs and technical landscape, support development and deployment of models
• Partner with internal infrastructure teams to integrate deep learning models with existing tools and systems
• Stay up to date with the latest advances in ML infrastructure and MLOps to develop and maintain efficient systems

Technologies We Use

• Programming languages: Python / Java
• Deep learning frameworks: PyTorch / Hugging Face / DeepSpeed
• Inference engine: ONNX / TensorRT
• Web-service protocols: RESTful / gRPC
• Cloud-based technologies: Docker / Kubernetes

What We Value

• Background in natural language processing and deep learning, experience with large language models
• Proficiency with any of the major deep learning frameworks
• Experience designing and implementing ML infrastructure to train and deploy large language models
• Experience with cloud-based platforms and tools
• Excellent communication and problem solving skills, ability to work independently and as part of a team

What We Require

• At least two years of experience in backend development with an emphasis on deploying deep learning models in production
• MS in Computer Science or related fields

Our benefits aim to promote health and wellbeing across all areas of Palantirians’ lives. We work to continuously improve our offerings and listen to our community as we design and update them. The list below details our available benefits and some of the perks that can be enjoyed as an employee of Palantir Technologies.

Benefits

• Employees (and their families) are eligible to enroll in: medical, dental, and vision insurance, life and disability coverage
• Paid leave for new parents and emergency back-up care for all parents
• Family planning support, including fertility, adoption, and surrogacy assistance
• Stipend to help with expenses that come with a new child
• Commuter benefits
• Relocation assistance
• Unlimited paid time off
• 2 weeks paid time off built into the end of each year
• 12 paid holidays throughout the calendar year
• Generous unlimited sick leave policy
• Employees are able to enroll in our company’s 401k plan

Salary

The estimated salary range for this position is estimated to be $125,000 - $200,000/year. Total compensation for this position may also include Restricted Stock units, sign-on bonus and other potential future incentives. Further note that total compensation for this position will be determined by candidate’s relevant qualifications, work experience, skills, and other factors. This estimate excludes the value of any potential sign-on bonus; the value of any benefits offered; and the potential future value of any long-term incentives.