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Machine Learning (ML) Engineer I

Parexel
Uxbridge
1 year ago
Applications closed

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When our values align, there's no limit to what we can achieve.
 

Parexel is in the business of improving the world’s health. We do this by providing a suite of biopharmaceutical services that help clients across the globe transform scientific discoveries into new treatments. We believe in our values,

This role will work within ourdepartment which is an innovative team that will build and deploy leading AI-driven solutions to improve workflows common across both Parexel and the life sciences industry. The team partner and support the business in building best-in-class AI-driven solutions when nothing suitable exists.

This role is to be based in the and can be either The office is open planned, and you will be working in an innovative and collaborative environment with your international peers and colleagues.

As the you will be responsible for developing AI Labs’ machine learning platform and creating production ready AI-based solutions for key impact areas in Parexel’s business. In this role, you will write, test, and release code and internal libraries according to the technology and productroadmaps. You will work collaboratively with application engineering, product, and business stakeholders to develop principled and innovative ML solutions from research to POC to production. You will also serve as experts within Parexel, driving AI education and providing expert guidance to other parts of the business.

Key Accountabilities: 

ML and Natural Language Processing (NLP) Technology

Leverage proprietary technology stack to build custom machine learning models

Design, implement, and document new ML/NLP modeling techniques and strategies

Develop Back-end / server-side software to support AI solution development and serving

Build internal frameworks, libraries, and infrastructure to improve machine learning and NLP capabilities to allow for rapid prototyping and new product delivery

Review and adapt recent research in ML and NLP into prototypes and productionsolutions

Review and improve the code of other engineers to enhance ML quality and security

Applied ML POCs and Experimentation

Understand business needs and user workflows and interpret in the context of potential AI solutions

Develop custom models and AI/NLP solutions to address business needs

Lead experiment and evaluation design based on well-founded best practices in machine learning to ensure safe, effective, and principled AI development practices

Carry out AI solution prototyping and experimentation

AI-based Production Solutions

Collaborate with Product to define and implement features to satisfy customer requirements

Partner with application engineering to build high quality AI-based productionsoftware

Participate in planning and check-in meetings to identify customer needs, potential roadblocks and solutions and support the software solution lifecycle from an AI perspective

AI Expertise, Education, and Advocacy

Contribute to establishing standards of practice in applied ML/AI to the life sciences industry

Create educational content for the AI Center of Excellence and other contexts to improve AI literacy and guide appropriate AI usage and communication across the company

Act as an AI expert advisor across Parexel on behalf of AI Labs

Education:

Educated to Master’s or PhD level in engineering or computer science with a focus on Machine Learning(and NLP)or other equivalent qualification/experience.

Skills: 

Machine Learning, Natural Language Processing (NLP), Deep Learning,(building and deploying NLP systems)

Strong CS fundamentals including data structures, algorithms, and distributed systems

Theoretical and practical proficiency in probability, statistical NLP algorithms, and modern ML technologies, including: transformers, graphical models, information retrieval techniques, LLMs, time series models, Reinforcement Learning, etc

Strong software engineering fundamentals, including the ability to write production ready code, architect packages, and make sound architectural and procedural choices for effective shared codebases

Python and scientific computing packages (pytorch, numpy, scikit-learn, tensorflow)

Database technologies such asElasticSearch, Neo4j, and SQL

Excellent interpersonal, verbal, and written communication skills

A flexible attitude with respect to work assignments and new learning

Ability to manage multiple and varied tasks with enthusiasm and prioritize workload with attention to detail

Willingness to work in a matrix environment with a variety of nontechnical stakeholders and technical collaborators, and to value the importance of teamwork.

Knowledge and Experience: 

Intermediate previous NLP Engineer or Machine Learning Engineer experience working in a commercial environment is essential.

Intermediate level experience with the following tools: Git, Github, scientific computing packages (pytorch, numpy, tensorflow), AWS or Azure cloud platforms, JIRA, Confluence, Docker

Good expertise in the use of Python is essential.

Experience producing high quality code in a shared context

Up to date with state of the art in Machine Learning(and NLP techniques/models)

Experience conducting and publishing research in Machine Learning/AI(NLP)preferred

Intermediate experience owning the delivery of cutting-edge production-quality AI solutions and models

In return we will be able to offer you a structured career pathway and encouragement to develop within the role including awareness and understanding of the industry. You will be well supported and for your hard work you will be rewarded with a competitive base salary as well as a benefits package including holiday, private healthcare, dental insurance as well as other benefits that you would expect with a top company in the CRO Industry. 

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