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Machine Learning Engineer, Biological Sequence Design

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InstaDeep

2mo ago

  • Job
    Full-time
    Mid & Senior Level
  • Data
    Engineering
  • London
  • Quick Apply

AI generated summary

  • You need a Master's in Computational Science or similar, experience with Deep Learning frameworks, strong software engineering skills, and excellent communication abilities.
  • You will lead engineering for research projects, develop software solutions, collaborate on ML model scaling, manage biological data, and report findings both internally and externally.

Requirements

  • Masters-level degree in Computational Science, Machine Learning or a related scientific field.
  • Experience using Deep Learning frameworks like PyTorch, Tensorflow and/or Jax.
  • Strong software engineering experience (Object-Oriented Programming, Unit Testing, Profiling, CI, Docker) via previous work or contributions to open-source projects.
  • Excellent communication skills and collaborative spirit.

Responsibilities

  • Lead the engineering components of long-term research projects encompassing all stages of the project life-cycle. Responsibilities include data generation pipelines, database management, development and maintenance of codebases, as well as the design and execution of analysis pipelines and reporting mechanisms.
  • Collaborate closely with the Core ML and Engineering teams to integrate and optimise cutting-edge methodologies for the distribution and scaling of large-scale (billion parameter plus) ML models.
  • Align with engineering leads across other critical projects to improve standardisation and methodological best practices across the company.
  • Develop and maintain robust, high-quality software solutions. Ensure code is modular, well-documented, and integrates smoothly with continuous integration systems.
  • Work in collaboration with Research Scientists, Engineers, and technical leads from various projects to uphold high coding standards and foster standardisation and methodological best practices across the Research Team.
  • Deploy machine learning models and associated processes across large-scale, distributed computing infrastructures, including CPUs, GPUs, and TPUs, utilising both in-house and cloud-based platforms.
  • Manage the efficient, reproducible, and performant handling of complex, multi-modal biological data. This includes optimising data generation, storage, and retrieval processes, particularly through advanced database management systems like SQL.
  • Actively contribute to the team's research initiatives, including publishing results and participating in open-source projects.
  • Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing.

FAQs

What is the job title for this position?

The job title is Machine Learning Engineer, Biological Sequence Design.

Where is the position located?

The position is located in London.

What type of company is InstaDeep?

InstaDeep is a pioneering AI company at the forefront of innovation, collaborating with major organizations like Google DeepMind and leading educational institutions.

What areas will the ML Engineer be working in?

The ML Engineer will be working at the intersection of machine learning and biology, specifically addressing challenges in biological sequence design.

What responsibilities will the ML Engineer have?

Responsibilities include leading engineering components of research projects, collaborating with ML and Engineering teams, developing software solutions, deploying ML models, managing biological data, and contributing to research initiatives.

What educational background is required for this role?

A Masters-level degree in Computational Science, Machine Learning, or a related scientific field is required.

What specific technical skills are needed for this position?

Experience with Deep Learning frameworks like PyTorch, TensorFlow, or Jax, and strong software engineering skills, including Object-Oriented Programming and CI, are needed.

Is experience in computational biology necessary?

While computational biology experience is a desirable bonus, it is not mandatory for the position.

What is the work model at InstaDeep?

InstaDeep operates on a hybrid work model, encouraging employees to work in the office at least 2 to 3 days per week.

Are there opportunities for career development in this role?

Yes, there are opportunities for career development, including active contributions to research initiatives and participation in published works.

Is the company committed to diversity and inclusion?

Yes, InstaDeep is committed to creating an authentic environment that celebrates diversity and encourages applications from underrepresented groups.

Do I need a legal right to work in the location I am applying for?

Yes, you will require the legal right to work in the location you are applying for.

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InstaDeep

Accelerate the transition to an AI-first world that benefits everyone

Technology
Industry
51-200
Employees
2014
Founded Year

Mission & Purpose

InstaDeep is a leading global technology company offering a range of AI solutions, ranging from optimized pattern-recognition, GPU-accelerated insights, to self-learning decision making systems. - Decision-making systems: Life and business are all about decisions. InstaDeep harnesses the power of reinforcement learning to create systems that can make decisions on their own, based on their own autonomous training. Many fields can benefit greatly from this technology, be it robotics, mobility, logistics, finance or healthcare. - GPU-accelerated insights: When you try to deploy AI in your business, compute power is key. A Multi-GPU setup can be messy and complicated. With Nvidia’s DGX-1 (one of the most powerful AI machines on the market), InstaDeep can help you achieve insane computing power to solve even the most intensive AI problems. - Optimized Deep Learning: Deep Learning delivers high-performance AI for pattern recognition yet is notoriously time-consuming to fine-tune. InstaDeep boosts this process to save you time and money on your computer vision, natural language processing or predictive analytics project.