Machine Learning Engineer (Life Sciences, Bio Medical, Bio Informatics, BioTech)

Overview

Remote
Depends on Experience
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Machine Learning Engineer
Machine Learning
Artificial Intelligence
Drug Discovery
Python
MLOps
Deep Learning
Data Science
Healthcare
Pharmaceuticals
Biotechnology
Computational Biology
Bioinformatics
Algorithms
Computer science
JAX
Machine Learning Operations (ML Ops)
Machine Learning (ML)
Statistics
PyTorch
TensorFlow
High performance computing
Research

Job Details

Machine Learning Engineer

About the Role:

  • We are seeking a highly motivated and skilled Machine Learning Engineer to join our growing team.
  • As a Machine Learning Engineer, you will play a crucial role in developing and implementing cutting-edge machine learning algorithms and systems to revolutionize the drug discovery process.
  • This role offers a unique opportunity to work on challenging problems with the potential to significantly impact patient lives.
  • Prior experience in Research and Development related to Life Sciences, BioTech, Drug Discovery is highly desired

Responsibilities:

  • Develop and deploy machine learning models in production environments, collaborating with engineers to ensure solutions are scalable, reliable, and adhere to best practices.
  • Tackle core research engineering challenges, encompassing the design, implementation, and scaling of machine learning algorithms.
  • Collaborate effectively with cross-functional teams, including research scientists, computational biologists, and data engineers, to solve complex problems.
  • Develop solutions enabling stakeholders to interact with and analyze diverse datasets.

Qualifications:

  • Education: Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, Physics, or a related field. A graduate degree is preferred.
  • Experience: A minimum of four years of proven experience in developing and applying machine learning models within an industry setting.

Required Technical Skills:

  • Programming Language: Proficiency in Python is essential.
  • Machine Learning Tools: Experience with Weights and Biases is required.
  • MLOps: Proficiency in MLOps workflows, including code version control, high-performance computing infrastructures, and machine learning experiment monitoring workflows.
  • Frameworks and Libraries: Extensive experience with machine learning frameworks and libraries such as JAX, PyTorch, PyTorch Lightning, and TensorFlow.
  • Theoretical Foundation: Strong background in statistics, probabilistic modeling, and data analysis.

Essential Soft Skills:

  • Communication: Excellent communication skills, with the ability to effectively convey technical concepts to both technical and non-technical audiences, including interactions with scientific and engineering leadership.
  • Collaboration: Proven experience collaborating with external scientific partners, including academic institutions and industry research groups.
  • Problem-Solving: A passion for tackling complex technical problems and a commitment to staying abreast of the latest advancements in machine learning.

 

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