Job roles: Machine Learning Engineer
Experience level: Senior, Lead
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
We’re looking for….
- Someone who wants to build a career in AI/ML. A self-motivated individual who is an expert in this technology.
- Someone humble who is excited to join a scale-up, is passionate and loves fixing problems.
- Someone who wants to be hands-on. While architecture and strategy are part of the job, you will be expected to write world-class production software at Zilch.
- Someone comfortable working on rapidly changing tools, best practices, architectures and code bases.
- An engineer who is proud about their pragmatic solutions.
Day-to-day responsibilities will include:
- Design the data pipelines and engineering infrastructure to support our enterprise machine learning systems at scale.
- Work with Data Scientists to take offline models Data Scientists build and turn them into a real machine learning production system.
- Develop and deploy scalable tools and services to handle machine learning training and inferences.
Key requirements:
- 5+ years of experience building end-to-end systems as a Platform Engineer, MLOPs Engineer, or Data Engineer (or equivalent).
- 5+ years of software engineering skills in complex, python systems.
- 3+ years of experience working with AWS tech stack and database systems.
- 3+ years of experience building custom integrations between cloud-based systems using APIs.
- 3+ years of experience developing and maintaining ML systems built with AWS Sagemaker (or similar).
- 2+ years of experience with at least one IaC technology (terraform, etc...)
- Experience developing with containers and Kubernetes in cloud computing environments.
- Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.)..
- Ability to translate business needs to technical requirements.
- Strong understanding of software testing, benchmarking, and continuous integration.
- Strong understanding of machine learning methodology and best practices.
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc.)
Bonus skills:
- A financial technology background, e.g. risk, finance, credit
- Experience with real-time distributed queuing solutions (e.g., SQS or Kafka)
- Experience with CI/CD tools (I.E. Bitbucket pipelines)
- Experience with transformation tools (I.E. DBT)Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems.
- Apply software engineering rigour and best practices to machine learning, including CI/CD, automation, etc.
- Support model development, with an emphasis on auditability, versioning, and data security.
- Facilitate the development and deployment of proof-of-concept machine learning systems.
- Communicate with stakeholders to build requirements and track progress.
Company Benefits
- Income protection - long term injury or illness the company will pay 75% of your base salary for up to 5 years
- Pension scheme, 5% employee contribution and 3% employer contribution
- 26 days holiday
- Family friendly policy
- Maternity - 6 months full pay and return to work bonus
- Paternity - 6 weeks full pay
- Enhanced Shared Parental Leave Pay and return to work bonus
- Enhanced Adoption Pay and return to work bonus
- Death in Service - 3x your annual basic salary up to £550k - complete expression of wish form
- Private medical insurance
- Specialist referrals
- Counselling / Talking Therapy / CBT
- Dental
- Optical
- Physiotherapy / osteopathy
- Cancer cover
- Virtual Doctor Online - online GP appointments within 2 hours
- Gym membership discounts
- £200 joining bonus for WFH set up on Zilch app
- Learning & Development - company support for professional qualifications and learning development
- Employee assistance programme
- Legal advice
- Financial advice (including mortgage advice)
- Childcare support
- Relocation advice
- Lifework perks - online cash back at over 1200 brands, cinema discounts, digital gift cards
- Hybrid working
- Casual dress code
- Work related social events
- Free fruit, snacks, and refreshments in the office (and in office barista)
- Opportunities to work from overseas offices
- Office breakout zone, including table tennis, pool, and comfortable seating
Interview Process
- 1st stage - initial screen
- 2nd stage - Hiring Manager intro
- 3rd stage - Technical test - remote
- 4th stage - On-site technical F2F