(Senior) Machine Learning Engineer
4 weeks ago
Job Description Are you an experienced Senior Machine Learning Engineer who wants to work in a team at the cutting edge of engineering sustainability?
Our client is on a mission to empower engineers to use AI to overcome their most difficult physics and design challenges and build truly great products. In light of this, they are recruiting a Senior Machine Learning Engineer to continue their growth and improve the capabilities of their products.
This well-funded company was founded in 2016, and provides a no-code AI platform to engineers to help them improve and accelerate the process of design and development. The company has grown steadily year on year and fosters a passionate, engaging and collaborative culture. They are proud to be an equal opportunity employer, valuing diversity and inclusion. The company's office is based in London Bridge and most employees are in the office 3 days per week.
As Senior Machine Learning Engineer, you will sit within the company's Data Science team and report to the Director of Engineering. Their Machine Learning stack runs on on-demand containerised infrastructure – ranging from sub-second latency functions to longer-running batch computer and higher-demand dedicated instances.
They run on AWS and soon Azure, with plans to also add GCP and on-prem. Python, Flask, Redis, Postgres, React, Plotly, Docker. AWS Athena SQL, Athena & EMR Spark, ECS Fargate; Azure Synapse/Data Lake Analytics, HDInsight.
Lead the productionisation of Monolith’s ML models and data processing pipelines, both mid-low-level system and design and exemplary hands-on implementations using Spark and other tech stacks
Shape the ML engineering culture and practices around model & data versioning, scalability, model benchmarking, ML-specific branching & release strategy
Proactively identify blockers across the team, help promptly and effectively to unblock them
7+ years' coding experience, including 3 years in a dedicated ML Engineering role
~Experience working with GB+ scale data
~ Experience deploying multiple ML projects across different environments
~ Productionisation experience in at least one cloud infrastructure (AWS, Azure, GCP)
~ Excellent communicator, able to relate confidently with colleagues at every level from junior developers to senior leaders
~ Distributed machine learning (Spark distributors, Horovod, native distributed on PyTorch or Tensorflow)
COMPENSATION/BENEFITS :
~£100k salary (or more depending on experience) + equity
~30 days annual leave + UK bank holidays
~ Pension with NEST
~ Vitality health insurance
~
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