Machine Learning Engineer
Datatonic, Switzerland
Job Description
As Google Cloud's premier partner in AI, Datatonic provides world-class businesses with cutting-edge data solutions in the cloud.
We help clients take leading technology to the limits by combining our expertise in machine learning, data engineering, and analytics. With Google Cloud Platform as our foundation, we help businesses future-proof their solutions, deepen their understanding of consumers, increase competitive advantage and unlock operational efficiencies.
Our team consists of experts in machine learning, data science, software engineering, mathematics, and design. We share a passion for data amp; analysis, operate at the cutting edge, and believe in a pragmatic approach to solving hard problems.
The Role
As a Machine Learning Engineer, you'll know how to engineer beautiful code in Python and take pride in what you produce. You'll be an advocate of high-quality engineering and best-practice in production software as well as rapid prototypes.
Whilst the position is a hands-on technical role, we'd be particularly interested to find candidates with a desire to lead projects and take an active role in leading client discussions. Your responsibilities will involve building trusted relationships with prospects, finding creative ways to use machine learning to solve problems, scoping projects, and overseeing the delivery of these engagements.
To be successful, you will need strong ML amp; Data Science fundamentals and will know the right tools and approach for each ML use case. You'll be comfortable with model optimisation and deployment tools and practices. Furthermore, you'll also need excellent communication and consulting skills, with the desire to meet real business needs and deliver innovative solutions using AI amp; Cloud.
Your responsibilities will include:
- Taking vague requirements and translating them into models that solve real-world problems
- Running machine learning experiments using a programming language with machine learning libraries.
- Optimizing solutions for performance and scalability.
- Implementing custom machine learning code.
- Data engineering, i.e. ensuring a good data flow between database and backend systems.
- Data science, i.e. analyzing data and coming up with use cases
- MLOps, i.e. automating ML workflows with testing, reproducibility and metadata/feature storage; Designing ML architectures on GCP
Requirements
- Multiple years experience as an ML Engineer, ideally from a consulting background.
- This candidate should be comfortable working with python as a backend language, delivering code in well-tested CI/CD pipelines.
- Familiarity with cloud environments (GCP, AWS, Azure).
- Experience with Software Engineering.
- Good knowledge of SQL.
- Knowledge of scaling up computations (GPUs, distributed computing, ..).
- Familiarity exposing ML components through web services or wrappers (e.g. Flask in Python).
- Strong communication and presentation skills.
Benefits
The Basics: 25 days holiday in addition to bank holidays, choice of laptop, 100 home equipment allowance
Health amp; Wellbeing: Employee Assistance Program, Health Insurance Allowance
Learning: Datatonic encourages continuous learning at all levels with a generous conference budget, freedom to explore the latest tools and technologies as well as regular knowledge-sharing activities. You will get access to Linux Academy, Coursera, and LinkedIn Learning and a 700 Conference Budget with 4 days of attendance per year
Career Development: A personalised development plan to ensure you hit your professional goals with a clear roadmap for progression
Impact: The opportunity to work on cutting-edge AI and ML solutions spanning multiple industries and with market-leading organisations
Innovation: Access to Datatonic LABs, our Research amp; Development hub. Experiment and bring forward ideas, create impactful and meaningful work in a creative and collaborative environment - even just for fun!
Team Vibe amp; Social: A welcoming and friendly team plus regular monthly social events
Our UK headquarters is based in a tech-centric environment in the centre of Canary Wharf. We also have offices in Stockholm, Geneva, Munich, and Barcelona, and we work with clients in many other European countries. We allow for flexible working hours and the possibility of remote work.
We’re an eclectic team with lots of different interests and personalities. We have many different roles across data science, engineering, analytics, consulting, marketing, business development, and operations. As a company, we have a strong empha