Senior Machine Learning Engineer

Senior MLOps Engineer Andela Location Requirement: India About Andela Andela exists to connect brilliance and opportunity. Since 2014, we have been dedicated to breaking down global barriers and accelerating the future of work for both technologists and organizations around the world. For technologists, Andela offers competitive long-term career opportunities with leading organizations, access to a global community of professionals, and educational opportunities with leading technology providers. At Andela, we’re deeply passionate about creating long-lasting and transformative growth opportunities for all - and doing it in an E.P.I.C. way! We’re excited to continue building our remote-first team with incredible people like you. After applying for this role, you will join our Andela Community of brilliant technologists by passing a technical screening and live interview. As a community member, you’ll have access to many exclusive technologist roles. Join Andela today to access this opportunity and more in our global marketplace! Our roles are typically filled at lightning speed, so if you’re considering applying, get your application in quickly! Andela´s Benefits: -- 100% payment in USD. This is a fully remote opportunity for one of our esteemed clients. About the role We are looking for a talented and passionate ML Engineer to join our client’s AI team. Our mission is to build predictive solutions that focus on business needs. You will be working closely with each team member to understand the team’s overall strategy and direction and provide your ML expertise in collaborating to design, build, deploy, and operate production pipelines and systems. The ideal candidate will be: Problem solver: you excel at understanding and solving complex problems in a proactive way. Quality communicator: you can break down complex or difficult topics and present these verbally, and in writing Ownership: you love handling owning and improving AI solutions Sharing: you're excited by the opportunity to set up best practices for the team through leading by example and promoting culture change Curiosity: you are innately curious and have a passion for learning new things. Passionate: you have a passion for all things AI and ML and want to share that with the team Responsibilities Contribute to the MLOps culture and practices enabling the team to create solutions with less friction and solid security, and reliability. Add expertise on ML Pipelines (Model serving, Model performance monitoring) Contribute to design, refinements, optimizations, and scalability for systems operating machine learning pipelines at web scales Build and lead building automated deployments and operations of AI based solutions Work directly with team to enable successful deployments and maintainable production systems. Qualifications Bachelor’s degree in a STEM field such as Statistics, Math, Engineering, Information Systems, etc. Experience with MLOps lifecycle management Docker and containerization. Python production level coding, including best practices Cloud platforms (e.g., AWS, GCP, and/or Azure) with experience with ML & Data offerings operating and deploying solutions using AWS Service including, but not limited to, S3, EKS, EMR, Athena, Glue, Lambda, Kinesis, MSK, Sagemaker, SQS and SNS (or correlated offerings on other cloud platforms). CI/CD tools (e.g., Jenkins, TravisCI, Bamboo). Good communication and presentation skills to explain technical solutions to either technical peers or non-technical stakeholders. Willingness to collaborate with colleagues to achieve repeatable high-quality outcomes as a team. Preferred Qualifications Master’s degree in a STEM field such as Statistics, Math, Engineering, Information Systems, etc. Kubernetes and container orchestration platforms. Infrastructure-as-code (e.g., Terraform, Ansible, Chef). Apache spark Airflow Certification in cloud platforms such as AWS, GCP, and/or Azure. Understanding of test-driven development. Willingness to improve test coverage of existing codebase. Required skills Machine Learning (7 - 9 yrs) AWS (Amazon Web Services) (7 - 9 yrs) Data Science (7 - 9 yrs) Docker (7 - 9 yrs) Python (7 - 9 yrs) SQL (7 - 9 yrs) Optional skills Apache Airflow (4 - 6 yrs) Apache Spark (4 - 6 yrs) Kubernetes (4 - 6 yrs) Terraform (4 - 6 yrs) Must have: Python (production level coding and best practices), SQL, full MLOps lifecycle, Docker, CI/CD, AWS (Sagemaker, S3, etc) or equivalent Nice to have: Terraform, Kubernetes, Spark, Airflow, Cloud certifications Main job time zone: EST Time zone overlap requirements: 5+ hours with EST (9 am - 2 pm) Location Requirements: India Working hours: Full-time dedication (8 hours/Day - 40 hours/week) Important: this role requires in-person work once a quarter for a few days (approximately a week). Exact dates and location to be confirmed. Device: Laptop to be provided by Andela (either shipped or stipend to purchase, in this case a receipt must be provided) Offer Estimated Duration: 12-month-term contractor position (Renewable) Full-time dedication (40 hours/week) At Andela, we know our strengths lie in our diverse community whose talents, perspectives, backgrounds, and orientations we take pride in. Andela is committed to nurturing a work environment where all individuals are treated with respect and dignity. Everyone has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits discriminatory practices. Andela provides equal employment opportunities to all employees and applicants without regard to factors including but not limited to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, pregnancy (including breastfeeding), genetic information, HIV/AIDS or any other medical status, family or parental status, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state and local laws. This commitment applies to all terms and conditions of employment, including but not limited to hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Our policies expressly prohibit any form of harassment and/or discrimination, as stated above. Andela is home for all. Come as you are.