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Staff Machine Learning Engineer - Job Opportunity at Altos Labs

Cambridge, United Kingdom
Full-time
Senior
Posted: March 18, 2025
On-site
GBP 113,900 - 174,800 per year

Benefits

Comprehensive healthcare plans typical of biotech sector
Career development in cutting-edge research environment
Collaborative scientific environment with world-class researchers
Work on transformative health technologies
Equal employment opportunity policies
COVID-19 vaccination program

Key Responsibilities

Design and implement large-scale ML algorithms for biological datasets with direct therapeutic impact
Partner with scientific teams to generate insights for novel therapy development
Lead development of generative AI/ML models for multi-modal biological applications
Scale and optimize machine learning models across distributed systems
Drive collaboration with internal and external research partners

Requirements

Education

Masters or Ph.D. degree in quantitative/computational field

Experience

Senior level experience in ML development

Required Skills

Expertise in generative models, language models, computer vision, bayesian inference Production-quality code development Multi-GPU and distributed training Python and deep learning libraries (PyTorch, JAX) Large-scale distributed optimization Collaborative teamwork Growth mindset
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Sauge AI Market Intelligence

Industry Trends

The convergence of AI and biotechnology is creating unprecedented demand for ML engineers with biological domain expertise Increasing focus on generative AI applications in drug discovery and therapeutic development Growing investment in computational approaches to aging and longevity research Shift towards multi-modal biological data integration requiring sophisticated ML approaches

Salary Evaluation

The offered salary range is competitive for the UK biotech sector, slightly above market average for similar roles, reflecting the specialized nature of the position and Altos Labs' strong funding position

Role Significance

Likely part of a specialized ML team of 5-10 engineers within a larger multidisciplinary research group of 20-30 scientists
Senior technical position with significant influence on core research initiatives and therapeutic development strategies

Key Projects

Development of novel ML architectures for biological data interpretation Creation of predictive models for cell rejuvenation outcomes Integration of multi-modal biological data streams for therapeutic insights Scale-up of computational infrastructure for biological ML applications

Success Factors

Deep expertise in both ML frameworks and biological systems Ability to bridge technical and scientific domains Strong collaborative skills for cross-functional research teams Innovation mindset for novel therapeutic approaches Experience with large-scale distributed computing systems

Market Demand

Very high demand with limited talent pool due to specialized requirement combination of advanced ML expertise and biological systems understanding

Important Skills

Critical Skills

Advanced ML expertise with focus on biological applications Distributed computing and scalable system design Cross-functional collaboration and scientific communication

Beneficial Skills

Biological data format familiarity Drug discovery pipeline understanding Open-source development experience Low-level programming languages

Unique Aspects

Rare combination of cutting-edge ML application in novel biological domains
Direct impact on therapeutic development through computational approaches
Access to unique biological datasets and research infrastructure
Opportunity to shape emerging field of rejuvenation biology

Career Growth

2-4 years typical progression timeline given rapid industry advancement and company growth phase

Potential Next Roles

Principal Machine Learning Engineer Technical Director of AI/ML Chief AI Officer Head of Computational Biology

Company Overview

Altos Labs

Well-funded biotechnology company focused on cellular rejuvenation and longevity research with significant financial backing and prominent scientific leadership

Leading position in emerging longevity/rejuvenation biotechnology sector with strong competitive advantages in AI/ML integration
Strategic presence in Cambridge biotech hub with access to top academic and industry talent
Research-driven environment emphasizing scientific excellence, collaboration, and breakthrough innovation
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