The future of industrial operations, from automobile manufacturing to
renewable energy generation and anything in between, will be incredibly
connected, transparent, intelligent and autonomous as companies try to
produce more, quicker, at lower costs and better quality.
At the
heart of this transformation, also known as Industry 4.0, is the data
generated by billions of industrial sensors and IoT devices. This data
flows from machine to machine allowing them to communicate in real-time,
is used to tell us about machine and process performance and ultimately
feeds artificial intelligent models that unlock operational secrets
related to trends and anomalies and let us automate repetitive tasks.
Smartia is leading the charge in artificial intelligence solutions for industry.
We
are building MAIO, an AI and data framework that is all about
collecting industrial data from various assets and then unleashing the
necessary analytics, artificial intelligence, machine learning or
cognitive work to predict equipment failures, streamline production
processes and uncover the hidden trends in production processes.
MAIO
is the digital backbone that connects machines, people and artificial
intelligence to help gain transparency and predictability of industrial
operations.
We are looking for a Machine Learning (ML) Engineer
to join our Engineering team and help us create the artificial
intelligence backbone powering MAIO. Giving the security sensitive
nature of our customers, we offer product deployments on both the cloud
and on-premise. This makes the deployment challenging as by design, we
can't be tied to a single cloud solution provider. Regarding the machine
learning infrastructure, we need to be able to deploy AI/ML models
seamlessly both at the edge and the cloud. For this role, you'll need to
be familiar with deploying AI/ML in production and building a solid
infrastructure around it. If you love the challenge and want to shape
the course of AI adoption in the industrial domain, we'd like to meet
you.
Responsibilities
----------------------
- Design and build machine learning systems
- Research and implement appropriate ML algorithms and tools in production
- Develop industrial machine learning applications in collaboration with our data scientists
- Automate machine learning tests and experiments
- Automate workflow for training and retraining AI/ML systems
- Extend existing ML libraries and frameworks
- Keep abreast of developments in the field
Requirements
--------------------
We
have a wide tech stack which starts with moving data out of the factory
using gateway devices (i.e. pocket sized computers) installed at the
client’s premises, we then persist the data in a data lake and move it
through various queues into specialised databases which make it easily
accessible. A backend makes the data available to either a frontend
where it can be explored by the user or to artificial intelligence
services which train various machine learning models. We already use
automated scripts to do cloud or on-premise deployments of the stack.
Our
AI/ML architecture is a key component of MAIO and will work in
conjunction with the suite of services powering the above workflow. For
this role, we expect you to have the following skillset:
- Will to make a difference
- Proven experience as a Machine Learning Engineer or similar role
- Understanding of data structures, data modelling and software architecture
- Deep knowledge of maths, probability, statistics and algorithms
- Ability to write robust code in Python
- Familiarity with machine learning frameworks (Keras, PyTorch, TensorFlow) and libraries (scikit-learn)
- Familiarity with MLOps tools (MLFlow, KubeFlow)
- Familiarity with container orchestration tools (Kubernetes, Docker)
- Excellent communication skills
- Ability to work in a team
- Outstanding analytical and problem-solving skills
Interesting
technologies that we either use or we like a lot (in no specific
order): Ansible, Vagrant, Proxmox, NiFi, MQTT, OPC-UA, Apache Hadoop,
Apache Kafka, Apache Druid, Kdb+, PostgreSQL, Git, Python, Django, Rust,
Protocol Buffers, REST, RPC, React, GraphQL, AWS, Azure, GCP,
Kubernetes, Docker.
The Smartians
--------------------
We
are a creative and ambitious bunch of engineers, hackers and
entrepreneurs who love building awesome technology that can make a
difference. Our skills range from robotics and AI to industrial
manufacturing and software engineering and have worked for some of the
largest organisations in these fields including Google, Airbus,
Rolls-Royce, Morgan Stanley and Ansys just to mention a few.
We
have one clear vision and we are using all the tricks in the book to get
there; we are highly collaborative, abuse the whiteboards, ask a lot of
questions and we are continuously trying to simplify and clarify the
steps needed to achieve our goals. We like to properly plan before
executing, we create engineering design documents, architecture models,
we prototype and only begin implementing once we reach consensus. We
embrace change, we adapt as we walk the path and we strive to grow the
team by hiring better, smarter people than us. We enjoy good as well as
bad jokes.
Benefits
------------
- Competitive salary
-
Flexible working hours and working from home on agreed days - because we
really believe in work-life balance and we want you to be happy
- Training and development programs
- Family healthcare cover
- Pension scheme
- Company profit-sharing scheme