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 & analysis, operate at the cutting edge,
and believe in a pragmatic approach to solving hard problems.
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
To be successful, you will need strong ML & 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
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
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.
The Basics: 25 days holiday in addition to bank holidays, choice
of laptop & pension scheme
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
Career Development: A personalised development plan to ensure
you hit your professional goals with a clear roadmap for
Impact: The opportunity to work on cutting-edge AI and ML
solutions spanning multiple industries and with market-leading
Innovation: Access to Datatonic LABs, our Research & Development
hub. Experiment and bring forward ideas, create impactful and
meaningful work in a creative and collaborative environment - even
just for fun!
Flexible Working: A mix of office and remote working
Team Vibe & Social: A welcoming and friendly team plus regular
monthly social events and team offsites (or remote events)
Working for Datatonic
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.
Were 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
emphasis on learning and professional development. Our core values
A hub for continuous learning, curiosity, developing ideas,
testing things out - and then putting excellence into practice.
Working collaboratively in cross-functional teams to achieve
customer delight. We love what we do and draw immense satisfaction
from taking responsibility and seeing the results of our work.
Creating positive change for our customers, using the most
relevant machine learning and analytics approaches and the best
technologies to meet real business needs.
Winning with Partners & Friends
Our business has been built on great partnerships and
open-source collaboration. Its one thing to be successful, but to
do it in partnership with great people and other great companies is
even better in our opinion.