Our mission: To be Earth's most customer-centric company.
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The Amazon ML Solutions Lab team enables AWS customers accelerate the use of machine learning and artificial intelligence to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Machine Learning Engineer with a strong background in machine learning and software development to help develop solutions by pushing the envelope in Time Series, Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
As an ML Solutions Lab Machine Learning Engineer, you are proficient in developing and deploying advanced ML models to solve diverse challenges and opportunities. You will be working alongside scientists with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You’ll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.
The primary responsibilities of this role are to:
- Invent, implement, and deploy innovative machine learning pipelines and systems to solve diverse challenges and opportunities across industries
- Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL systems to solve them
- Interact closely with account teams, researchers and scientists, and engineering teams to drive model implementations and new algorithms
Location flexibility: Open to multiple AWS U.S. West corporate office locations. This position requires travel of up to 20%.
- 4+ years of professional software development experience
- 3+ years of programming experience with at least one software programming language
- 2+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems
- Experience as a mentor, tech lead OR leading an engineering team
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field
- Strong understanding of machine learning fundamentals, with working knowledge of Python and experience with deep learning frameworks
- Relevant experience in deploying machine learning systems into production, including orchestrating batch and streaming pipelines
- Knowledge of data management fundamentals
- 2+ years of hands-on experience in model containerization, CI/CD pipelines, API development, model training and productionizing ML models
- Entrepreneurial spirit combined with strong architectural and problem-solving skills and experience in delivering end-to-end solutions
- Experience in building end to end ML engineering infrastructure
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
- Experiences related to machine learning, deep learning, NLP, CV, GNN, or distributed training
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Advanced knowledge of performance, scalability, enterprise system architecture, and engineering best practices
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.