Job description

  • 3+ years experience with ML hands-on and implementation of ML systems and models, 7+ years of professional experience in a business environment, 7+ years of experience of IT platform implementation in a highly technical or analytical role, 3+ years of experience handling large datasets
  • Strong software development skills with proficiency in one or more programming languages (Java, Scala, Python, etc.)
  • Experience with database flavors of RBDMS, NoSQL, or Graph
  • Strong understanding of DevOps practices with practical hands-on application
  • Strong interest in Machine Learning solutions Strong verbal and written communications skills and ability to lead effectively across organizations

Job summary
Possible locations: Stockholm
AWS Professional Services is a unique organization. Our customers are most-advanced companies in the world. We build for them world-class, -native IT solutions to solve real business problems and we help them get business outcomes with AWS. Our projects are often unique, one-of-a-kind endeavors that no one ever has done before.

At Amazon Web Services (AWS), we are helping large enterprises build ML models on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. AWS Professional Services works together with AWS customers to address their business needs using AI solutions.

As a Machine Learning Engineer Consultant, you will innovate, (re)design and build -native, business-critical ML/data solutions with our customers. You will take advantage of the global scale, elasticity, automation and high-availability features of the AWS platform. You will build customer solutions with Amazon Elastic Compute (EC2), Amazon Data Pipeline, Amazon S3, Glue, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, Amazon SageMaker, AWS Lake Formation and other AWS services.

You will collaborate across the whole AWS organization, with other consultants, customer teams and partners on proof-of-concepts, workshops and complex implementation projects. You will innovate and experiment to help Customers achieve their business outcomes and deliver production-ready solutions at global scale. You will lead projects independently but also work as a member of a larger team. Your role will be key to earning customer trust.

As an Amazonian you will demonstrate the Amazon Leadership Principles, coaching and mentoring others on best practices, performance and career development.

This is a customer-facing role. When appropriate and safe, you will be required to visit our office and to travel to client locations to deliver professional services when needed.
You will:
  • invent and build ML solutions that solve complex problems, scale globally, guarantee performance, and enable breakthrough innovations,
  • use AWS AI services (e.g., Personalize), ML platforms (SageMaker), and frameworks (e.g., MXNet, TensorFlow, PyTorch, SparkML, scikit-learn) to help our customers build ML models,
  • work with customers and partners, guiding them through planning, prioritization and delivery of complex transformation initiatives, while collaborating with relevant AWS Sales and Service Teams,
  • assist customers by being able to deliver a ML/data projects from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organization,
  • work with our other Professional Services consultants (Big Data, IoT, HPC) to analyze, extract, normalize, and label relevant data, and with our Professional Services engineers to operationalize customers’ models after they are prototyped,
  • help customers define their business outcomes and guide their technical architecture and investments,
  • create and apply frameworks, methods, best practices and artifacts that will guide our Customers; publish and present them in large forums and across various media platforms,
  • contribute to enhancing and improving AWS services.
Our team in AWS Professional Services provides you excellent opportunities to
  • build enterprise-scale ML systems hands-on on AWS,
  • work with an innovative companies, with great teammates, and have a lot of fun helping our customers. A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.
  • resolve technical challenges in AI/ML, big data, IoT, data science, and more,
  • overcome business challenges in different industries,
  • launch digital innovations with our Customers in-production,
  • develop your leadership skills in Customer engagements,
  • create pioneering innovation and influence our services in collaboration with the wider AWS organization,
  • influence AWS adoption in our regional market.

Come and Build with us!

  • 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
  • 3+ years of hands-on experience in implementation of Big Data systems like Hadoop/Spark clusters
  • 3+ years Application Development experience required with serverless technologies
  • Solid experience with Streaming technologies (Kafka, Kinesis, etc.)
  • 1+ years hands-on experience with MXNet, TensorFlow, or PyTorch
  • Experience training distributed ML models on CPU and GPU hardware
  • AWS Certification in DevOps Professional, Developer Associate or Specialty (Database, Data Analytics, Machine Learning)
  • Experience with IoT hands-on implementation (edge computing preferred)
  • Serving ML models through realtime APIs
  • Experience with deploying production-grade machine learning solutions on public cloud platforms

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect, use and transfer the personal data of our candidates.

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