About the job
As the tech firm that created the mobile world, and with more than 54,000 patents to our name, weve made it our business to make a mark. When joining our team at Ericsson you are empowered to learn, lead and perform at your best, shaping the future of technology. This is a place where you’re welcomed as your own perfectly unique self, and celebrated for the skills, talent, and perspective you bring to the team. Are you in?
Come, and be where it begins.
About This Opportunity
As a Machine Learning Engineer (MLE), will be leading efforts for AI model deployment at scale, involving edge interfacing, ML pipeline and design of supervising and alerting systems for ML models. A specialist software engineer with experience building large-scale systems and enjoys optimizing systems and evolving them.
We believe in trust we trust each other to do the right things. Therefore, we believe in taking decisions as close to the product and technical expertise as possible!
We truly believe in happiness, we enjoy and feel passionate about what we do and value each others technical competence deeply!
What You Will Do
Prioritize multiple productization/deployment projects within a certain product/business.
Manage communication, planning and collaboration with business
Design, and implement horizontally scalable solutions, optimizing insight delivery & exposing them as microservices.
Design & develop monitoring framework & demonstrate it to help fix/optimize deployments
Contribute to IP creation for Ericsson in AI/ML
You will bring
3+ years of demonstrated ability in the following:
Software/tools: Hadoop, Spark, Kafka, etc.
Relational SQL and NoSQL databases, including Postgres and Cassandra.
ML & data pipeline and workflow management tools: Azkaban, Luigi, Airflow, Dataiku, etc.
Stream-processing systems: Storm, Spark-Streaming, etc.
Object-oriented/object function scripting languages: Python, Java, Scala (Advanced level in one language, at least)
Experience deploying, debugging and optimizing ML models to handle & scale to Bigdata.
Experience developing SaaS with deep knowledge in designing for cloud
Good knowledge in algorithms & data structures, especially for handling large-scale data. Experience working in ML frameworks such as Tensorflow, PyTorch, etc
Experience converting code to work in parallel/distributed environments and deploy in edge – quantization of deep learning models, mobile/low footprint code development, etc.
Good understanding of model validation techniques/metrics
Solid grasp of message queuing, stream processing, and highly scalable BigData stores.
Experience with Docker containers, orchestration systems (e.g. Kubernetes), continuous integration and job schedulers. Experience with cloud native technologies, microservices design and REST APIs.
Knowledge of server-less architectures (e.g. Lambda, Kinesis, Glue).
Why Join Ericsson?
At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build never seen before solutions to some of the worlds toughest problems. You´ll be challenged, but you wont be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next.
What Happens once you apply?
Click Here to find all you need to know about what our typical hiring process looks like.
Encouraging a diverse and inclusive organization is core to our values at Ericsson, that’s why we nurture it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team.
Ericsson is proud to be an Equal Opportunity and Affirmative Action employer, learn more. We are committed to providing reasonable accommodations to all individuals participating in the application and interview process. If you need assistance or to request an accommodation due to a disability please reach out to email@example.com
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