THE ROLE
SFL Scientific is looking for a Senior DevOps Engineer to join our growing data engineering team and support our AI consulting practice. In this role, the ideal candidate will define, design, and develop solutions for multiple projects that leverage best practices and emerging DevOps, MLOps, and cloud solutions. The Senior DevOps Engineer will have the opportunity to work cross functionally with both internal and external stakeholders, be client facing, and develop production data and ML architectures.
As a Senior Engineer, you'll work as part of a team of data scientists, engineers, and technical leads to help to solve complex R&D and technical problems from strategy to execution with an emphasis on DevOps, CI/CD, and deployment performance. Key to this role is to develop and implement data pipelines across cloud, high-performance compute, and hybrid solutions. This includes creating custom solutions across data management, ingestion, automation, and streamlining IT infrastructure processes for organizations across a range of industries including healthcare, life sciences, manufacturing, energy, and more.
SFL Scientific is a US-based data science professional services firm focused on strategy, technology, and solving business & operational challenges with Artificial Intelligence. Working with clients of all sizes, industries, and AI maturity levels, our capabilities range from developing corporate AI strategy to building custom AI applications at scale. With a globally connected network of technology and cloud partners, SFL Scientific’s core services include leading cross-functional efforts across business, IT, and operations. Join us to expand your technical career through consulting and professional services; opportunities to develop data science & AI skills are available.
This is a full-time permanent position based out of our offices in Boston, MA, and is available for remote candidates in the United States.
RESPONSIBILITIES
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Work with clients to design, develop, and deploy new architectures for machine learning & automation applications such as ELT functions, HPC/compute infrastructure, hybrid cloud solutions, database management, and optimization of DevOps procedures
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Leverage advanced skills in modern data architecture, data engineering, data transformation, management of structured and unstructured data sources using cloud-native services or on-prem technologies
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Support and enhance data architecture, data pipelines, and define multiple database schemas (Graph DB, SQL, NoSQL) to develop algorithm scalability and deployment
based on agile business priorities and technology initiatives -
Assist in the development of a big data platforms using pipeline technologies such as Spark, Airflow, and more to support a variety of requirements and ensure solutions are designed for successful deployment, security, and high availability in the cloud or on-premise
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Adopt best engineering practices in automation, HPC, CI/CD, AIOps, and data solutions
QUALIFICATIONS
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Master’s degree in STEM field or equivalent experience
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5 years experience in data engineering, DevOps, or MLOps
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Expertise with AWS such as EC2, EBS, ELB, RDS, S3, Redshift, Lambda, etc
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Experience managing Docker, Kubernetes, Spark, Dask, Flask, and CI/CD services
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Experience with provisioning and configuration management tools; Puppet, Ansible, Chef, Airflow, Terraform, Jenkins etc.
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Database and data warehousing experience, relational and NoSQL databases
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Proficient of the various services and capabilities of computing platforms (AWS/Azure/GCP) with AWS/Azure certifications.
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Excellent verbal & written communication skills
BENEFITS
Base salary, performance bonus/compensation, medical coverage, 401k plan, paid time off (vacation, personal/sick, parental, etc.), flexible work schedule, ongoing industry training, and other company-wide perks.
GROWTH
This person will have a complete view of a growing consulting firm in a novel, technical field, working in a highly collaborative and responsive environment with high-profile Fortune 100 clients and partners. The candidate has the opportunity to shape how the data science team functions within SFL Scientific as the company expands based on client performance, project delivery, and technical solution development. This is an opportunity for a talented data engineer to grow into a manager role, develop professionally and help develop a cohesive team of engineers, consultants, and scientists to support AI development and services efforts.
A MESSAGE ON COVID-19
Our priority is to safeguard the health and well-being of our team members, our families, and communities. During this rapidly changing environment, we are closely monitoring COVID-19 developments and updating our response plan quarterly. To do so, we are regularly soliciting feedback from employees to help inform our return-to-office strategy and best accommodate working conditions individually. As we look forward to the potential of in-office meetings, either proof of vaccination, or a negative COVID-19 test will be required for all visiting employees based on the 9/9/2021 Federal Mandate.
Top Skills
What We Do
SFL Scientific is a US-based data science professional services firm focused on strategy, technology, and solving business & operational challenges with Artificial Intelligence. Working with clients of all sizes, industries, and AI maturity levels, our capabilities range from developing corporate AI strategy to building custom AI applications at scale. With a globally connected network of technology and cloud partners, SFL Scientific’s core services include leading cross-functional efforts across business, IT, and operations. Hundreds of clients—including S&P100 enterprises, fastest-growing startups, and government agencies—trust SFL Scientific to create and accelerate AI initiatives.
Why Work With Us
Gain a complete view of a growing consulting firm in a novel, technical field, working in a highly collaborative and responsive environment with high-profile Fortune 100 clients and partners. This is an opportunity for a talented data scientist to grow into a manager role, develop professionally and help develop a cohesive team of engineers.