Machine Learning Engineer - Remote UK/EEA
Contract to January 2022
Who are we?
We're a software development company building the world's Elastic Workforce, reinventing work and challenging the assumption that a local team = the best team.
We help businesses deliver technical projects better than ever before through our platform and on-demand Elastic Teams™. Customers use our platform to scope any software project and are then paired with a fully managed Elastic Team of the world's best permanent freelancers that deliver it.
We have recently secured £5m in Series A funding from Guinness Asset Management and are now hiring a number of exciting roles to add to our fully remote team for exceptional growth ahead.
As a member of the team, you'll be working with scientists, engineers, product managers, salespeople and operational leaders from a diverse set of backgrounds who are challenging every assumption about work.
Want to know more? read: https://distributed.co/about
Elastic Team Machine Learning Engineer
As a Distributed Elastic Team Machine Learning Engineer, you are responsible for a portfolio of technical projects and comfortable presenting ideas for system improvements. The role will focus on data science/machine learning/insights derivation. You’ll be heavily involved in collaboration with the end client’s scientists/engineers/stakeholders and the development team to ensure shared understanding and successful delivery of necessary/desired changes/improvements to the solution.
As a Machine Learning Engineer, you’ll be expected to undertake analysis, report findings, suggest improvements and implement changes.
Industry agnostic, our Elastic Teams have delivered products for everyone, from multinational banks to bleeding-edge tech start-ups building their first products.
We work in an Agile process as part of a cross functional team which includes backend & frontend specialists, QA and technical leads, project managers and client stakeholders. You’ll need to collaborate well with a DevOps lead and one (or more) other senior backend and/or DevOps Engineers for a complex IoT healthcare related solution deployed in AWS that aims to improve the quality of life for vulnerable and recovering people.
We work in a collaborative development environment where our team members help design, evolve and support the operation of our platforms.
Your day-to-day will be dynamic as you’ll be needed to support a range of activities within surfacing insights and ultimately within trial and production when the product is live. You’ll interface extensively with internal and client teams, implementing code to provide insights and machine learning.
- Machine Learning and particular concepts such as - shapely values, changepoint detection (PELT,) clustering algorithms, bias detection
- AWS - Sagemaker Studio (including pipelines, notebooks, endpoints, clarify,) Elasticache (Reds,) ECS, S3, DynamoDB, RDS, Lambda, CloudWatch
- Python 3.x - Ruptures, NumPy, matplotlib, Pandas, Sklearn, Boto3, Scipy
- DevOps experience and knowledge of how this can be applied to ML (MLOps)
- Python - Kmodes, Kneed, Pytest
- AWS - CDK
We’re looking for passionate technologists who enjoy working in collaborative agile teams. You’ll need to be a clear, concise & engaging communicator with people on your team (and the wider Distributed family.) We enjoy the big picture and the detail; we want people who excel at both. We need someone with a deep understanding of agile management (various projects simultaneously,) who can determine priorities/deadlines whilst working under pressure. Equally as important are soft skills - strong communication skills with the ability to collaborate.
Things to know:
Distributed is proud to be an Equal Opportunity and Affirmative Action Employer. We evaluate qualified applicants without regard to race, national origin, religion, sex, sexual orientation, gender identity, disability, protected veteran status, and other statuses protected by law.
By submitting your application you give us permission to store and use the information from your cv and your answers to application questions.