Senior Software Engineer - Machine Learning Pipelines

Overview

On Site
USD 170,000.00 - 220,000.00 per year
Full Time

Skills

Pivotal
IMPACT
Art
Design
Fusion
Management
Machine Learning (ML)
Software engineering
Artificial intelligence
Cadence
Data processing
Apache Spark
Real-time
Cloud computing
Amazon Web Services
Microsoft Azure
Docker
Kubernetes
Orchestration
Version control
Git
Continuous Integration and Development
Software deployment
Continuous integration
Continuous delivery
Python
SQL
Database
Data storage
PostgreSQL
MongoDB
Problem solving
Attention to detail
Innovation
Communication
Leadership
Google Cloud
Google Cloud Platform
Machine Learning Operations (ML Ops)
Debugging
Data
Geospatial analysis
Collaboration
Teamwork
Recruiting
LinkedIn
Facebook
Twitter
Energy
Commodities
Trading

Job Details

RWE Supply & Trading Americas, LLC
To start as soon as possible, fulltime, permanent


We are building our core AI Weather Lab team to explore creative applications of AI methods to challenges in the renewable energy industry. To help us innovate and build industry-leading AI models, we are seeking an experienced senior software engineer with a proved track record in designing and implementing production-grade pipelines for machine learning models.

As a leading member of our engineering team, you will play a pivotal role in architecting, developing, and optimizing end-to-end pipelines that enable the deployment and scaling of advanced machine learning solutions in real-world applications. The successful candidate will play a critical role in developing and maintaining the tech stack of the lab and will work with senior scientists and engineers from a variety of fields. RWE is the third-largest producer of wind power in the world, so you will have a material impact on renewable energy production across the globe.

Your future plans
  • If you're passionate about building scalable pipelines for state of the art production machine learning models and thrive in a fast-paced, collaborative environment, we'd love to hear from you! Your responsibilities will include:
  • Lead the design, development, and operation of complex machine learning and multi-faceted data fusion pipelines in a production environment
  • Collaborate closely with data scientists, machine learning engineers, and scientists to integrate machine learning models into scalable production systems
  • Develop and oversee reusable components, libraries, and frameworks to streamline pipeline development and maintenance
  • Optimize pipeline performance, reliability, and resource utilization
  • Stay on the forefront of advancements in machine learning technologies, cloud services, and software engineering best practices with an eye towards identifying and integrating exceptional new components into the AI lab's production repertoire
  • Forster a strong team culture where diverse viewpoints, backgrounds and expertise

Your powerful skills
  • 7+ years of experience building, deploying, and monitoring complex pipelines that operate at an hours-level cadence
  • Extensive experience in large scale data processing and distributed systems such as Apache Spark
  • Extensive experience in serverless computing and event-driven architectures for building scalable and cost-effective pipelines, including stream processing frameworks for real-time data ingestion and processing
  • Deep expertise in cloud computing platforms such as AWS, Azure, or Google Cloud Platform
  • Strong understanding of containerization technologies (Docker, Kubernetes) and orchestration tools
  • Proficiency with version control systems (e.g., Git), continuous integration/continuous deployment (CI/CD) pipelines, and infrastructure-as-code tools
  • Proficiency in Python and SQL
  • Proficiency in database technologies for data storage and retrieval (e.g., PostgreSQL, MongoDB, BigQuery)
  • Excellent problem-solving skills, attention to detail, and a passion for learning and innovation
  • Strong communication and leadership skills, with the ability to work effectively in cross-functional teams and contribute to a positive team climate

Advantageous, but not a must
  • Experience with Google Cloud Platform MLOps tools
  • Familiarity with monitoring, logging, and debugging tools for distributed systems (e.g., Prometheus, ELK Stack)
  • Understanding of security best practices for securing data pipelines
  • Expertise working with large geospatial weather and climate datasets as well as the Pangeo stack

Our offer

We really appreciate you going the extra mile and using every ounce of energy when the heat is on. That's why we want to make your time with us as enjoyable as possible. At RWE Supply & Trading we value our employees and strive to create a supportive and inclusive work environment. With a range of competitive benefits, we not only offer excellent development prospects and an attractive remuneration package, but also take care of your well-being and understand that life-work integration is essential. Also our offer includes the following perks:
  • Dynamic of a start-up in a well established environment
  • Using cutting edge technology to solve challenging matters
  • Contribution to the company goals of energy transition
  • Hybrid working model with 3 days in the office to foster collaboration and teamwork
  • Diverse and multicultural team in a highly dynamic and rapidly growing business
  • Salary range $170,000 - $220,000

rwe.com/career

Any questions? Patrycja Bartela (Recruiting), E:

Apply now with just a few clicks: ad code 87482

We look forward to meeting you!

We value diversity and therefore welcome all applications, irrespective of sex, disability, nationality, ethnic and social background, religion and beliefs, age or sexual orientation and identity. Of course, you can find us on LinkedIn, Facebook, Twitter and Xing, too.

RWE Supply & Trading is the interface between RWE and the energy markets around the world. Around 2,000 employees from over 70 different countries trade electricity, gas, commodities and CO2 emission allowances. The trading entity also ensures the commercial optimisation of RWE's power plant dispatch and markets electricity from RWE.
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