Research Engineer, Machine Learning and Computational Biology

InstaDeep

2mo ago

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

AI generated summary

You must have a Masters in Computational Science or related field, experience with Deep Learning frameworks, strong software engineering skills, and excellent communication. Additional experience in research teams, computational biology, and published papers is desirable.
You will lead engineering components of research projects, collaborate with ML and engineering teams, develop robust software solutions, deploy ML models on distributed infrastructures, manage complex biological data, contribute to research initiatives, and report findings effectively.

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.
Desirables:
Experience in professional research teams; either industrial or through PhD/post-doctoral positions.
Experience with computational biology or molecular dynamics.
Published scientific papers in related domains such as ML or bioinformatics.

Responsibilities

Lead the engineering components of long-term research projects encompassing all stages of the project lifecycle. 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 team 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 expertise is required for the Research Engineer, Machine Learning and Computational Biology position at InstaDeep?

The ideal candidate should have expertise in machine learning as well as experience in the curation of experimental data and computational modelling techniques such as homology modelling, molecular dynamics with classical force fields, and quantum chemistry calculations with density functional theory.

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.