Machine Learning Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Job summary
Are you excited about building software solutions around large, complex Machine Learning (ML) and Deep Learning (DL) systems? Want to help the largest global enterprises derive business value through the adoption and automation of Artificial Intelligence (AI)? Eager to learn from many different enterprises’ use cases of AWS ML and DL? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades - pioneering and shaping the world’s AI technology?

At Amazon Web Services (AWS), we’re hiring technical Machine Learning Developers to collaborate with our Data Scientists to deliver ground-breaking solutions for customers. We are looking for Engineers with Data Science experience and Data Scientists with Engineering experience to support our efforts in the Enterprise, IoT, and start-up communities. We want to take your full-stack Data Science know-how to a new level by empowering AWS customers to maximize the benefits they receive through AI/ML on the AWS platform. This means building and operationalizing ML and DL solutions for our customers while helping them adopt modern Machine Learning best practices throughout every stage of their model development lifecycle.

AWS Professional Services is a unique consulting team. We pride ourselves on being customer obsessed and highly focused on the ML enablement of our customers. If you have experience with ML, including building, deploying, and monitoring models, we’d like you to join our team. A familiarity with cloud solutions (not necessarily AWS) and DevOps best practices is key as you will work with teams of Data Scientists, Data Engineers, and Architects to build truly end-to-end solutions. Without exception, you MUST be prepared and eager to learn new technologies in this role.

You will provide deep and broad insight to customers and partners to help remove constraints that prevent them from leveraging AWS services to create strategic value. A commitment to team work, hustle, and communication skills are important in this role. Creating reliable, scalable, and high-performance AI/ML solutions requires strong technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience building large-scale distributed systems.

About the team
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. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• Bachelors degree in computer science, engineering, data science, or related technical, math, or scientific field
• 4+ years of industry experience developing applications, designing data architectures (e.g. data pipelines, distributed computing engines, ML infrastructure design), or writing software using scripting languages (e.g. Python, R), database languages (e.g. SQL, PL/SQL, PG-PL/SQL), and version control
• Experience training and hosting various types of ML algorithms
• Experience using data science tools, libraries, and frameworks (e.g. Scikit-learn, caret, mlr, mllib, SparkML, NumPy, SciPy, Pandas, TensorFlow, PyTorch, MXNet)

PREFERRED QUALIFICATIONS

• Masters degree in computer science, engineering, data science, or related technical, math, or scientific field
• 2+ years experience performing Data Scientist duties (e.g. ML algorithm selection, feature engineering, model training, hyperparameter tuning, distributed model training, supervised and unsupervised learning implementation, building model pipelines, using Machine Learning tools/libraries/frameworks)
• 2+ years MLOps experience (e.g. model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning)
• Experience creating orchestration workflows with tools such as Airflow, Kubeflow, or AWS Step Functions
• DevOps experience (e.g. CI/CD Pipelines, Infrastructure as Code, containers, Agile software development)
• Experience implementing IoT solutions such as edge computing
• Big Data batch and real time data processing experience (e.g. Hadoop, Spark , Presto, Kafka, Kinesis, Flink)
• Experience writing production-level code using object-oriented design (OOD) best practices
• Experience employing test-driven development (TDD)
• Experience handling terabyte size datasets