At the moment we are looking for experienced MLOps Engineer to strengthen our Abu Dhabi team. You would start your journey in one of our most interesting and challenging projects with the role covering the following aspects:
Development of big data solutions for data collection from embedded / IoT devices.
Your future colleagues are waiting for you to join our international team. Working with us is uncomplicated, there’s a good team spirit, low-hierarchy and nonexistent bureaucracy. Our way of working is flexible too, many of our team work remotely from home with visits to our office from time to time when needed. This role is equally challenging, and as such we offer a very good compensation. We will provide help for you (and your family) in relocating and settling in to Abu Dhabi. We would hope that you are able to start as soon as possible but we are of course ready to be flexible also.
REQUIRED QUALIFICATIONS
The software professional we are looking for should be comfortable with at least some of the following:
Experience (5+ years) in the field of ML Engineering and MLops.
Excellent programming skills in Python. React.js, Node.js, Typescript
Deep knowledge of working with high volume and velocity data sets relevant to the intrusion detection system for IoTs (NSL KDD etc..)
Proven data engineering experience on Lake solutions using Big Data Processing & Streaming Tools (e.g. Hadoop, Spark, Flink, Kinesis, Kafka, Hive, Presto), ELK (Elasticsearch, logstash, Kibana), RDBMS & NoSQL systems.
Knowledge in Data collection from Embedded devices (Sensors, Electronic Boards, the behaviour of Embedded devices CPUs, Peripherals etc..).
Deep understanding and implementation of big data analytics, database solutions, and management tools & technologies for embedded IoT systems.
Experience in MLOps with topics like automation, governance, and deployment.
Professional experience with cloud-based tools for machine learning and MLOps e.g., AWS SageMaker or Azure ML. Docker and Kubernetes is a plus
Experience in deployment of deep learning models for low-latency inference on dedicated edge devices (IoT devices).
Experience complex data-processing and machine-learning pipelines.
A knowledge of the Cybersecurity of IoTs and Backstage.io would be a plus.
WHY JOIN UNIKIE?
Build new solutions for our customers and work with cutting edge technologies?
Collaborate along with colleagues who are the top in their field and together with our customers to strive for understanding what they need?
Develop and challenge yourself and learn more from experienced software talents?
Work with modern technologies and be involved to solve complex difficult challenges our customers might be facing?
Have an excellent compensation for your work.
Work in a global environment that develops modern, secure solutions for pioneers in their field
Work in a flexible low-hierarchy organization that looks after its own
In addition to our customer deliveries, we focus on our own R&D, where you can bring your own expertise to if you want to
How to Apply
If this sparked your interest, please send your application to jobs@unikie.com Our recruitment team is happy to share you more information about Unikie and our open positions, so please drop us a line if you wish to discuss with us before sending your CV or have any questions in mind!
LOCATION
Abu Dhabi (UAE)
TAGS
Node.js, Python, Machine Learning, TypeScript, React.js, Big data, Cybersecurity, MLOps
About Unikie
Unikie, founded Unikie in 2015, is one of the fastest growing technology companies in Finland. We are Finnish forerunner in intelligent, real-time decision-making applications for vehicles, cars and industry. We develop technology that connects sensor data with steering and decision-making based on constant awareness over secure connections. Additionally, we offer consultation for developing customer-specific solutions. Our annual revenue in 2021 was MEUR 44. Our numbers are growing 400+ software professionals and enthusiasts with a deep internal flame for developing the best technology solutions together with our customers.
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