THE ROLE

SFL Scientific is hiring a Cloud Engineer in a technical development and consulting role as part of the data science group. The goal is to design and develop solutions for various organizations looking to develop architectures that enable tools, software, and processes that support machine learning and AI initiatives. The Cloud Engineer will work with clients in cloud development, automation, DevOps, data engineering, automating and streamlining IT infrastructure processes and tasks to develop systems for organizations in healthcare, life sciences, biotech, electronics, public sector, manufacturing, agriculture, and retail sectors.

Working with the technical team, the goal is to tackle and help organizations solve some of their most complex challenges with mathematics, data science, data engineering, and emerging technology. By being platform agnostic, the ideal candidate will recommend and develop the best technical solution for each client and problem. Opportunity to develop data science & Artificial Intelligence/Machine Learning skills available.

SFL Scientific is a data science consulting firm applying AI & machine learning to help organizations develop new tools and business opportunities. We offer research, professional services, and advisory services to companies in a wide set of industries.

To learn more visit https://sflscientific.com/careers

RESPONSIBILITIES

• Work with clients and their IT teams to design, develop, and deploy architectures for machine learning & AI applications

• Recommend and develop database architectures, ETL functions, compute infrastructure, scalability, and optimization of DevOps procedures

• Collaborate with colleagues to support and improve architecture, systems, processes, standards, and data engineering tools

• Participate in architectural discussions to ensure solutions are designed for successful deployment, security, and high availability in the cloud

• Write and maintain code for automating the creation of scalable/resilient systems/infrastructure

• Educate/mentor data scientists and teams on best practices

REQUIREMENTS

• Bachelor’s degree in physics, math, computer science, statistics, or related quantitative field, or equivalent experience. 

• Knowledge of the various services and capabilities of computing platforms (AWS, Azure, GCP).

• Expertise with AWS services, including IAM, EC2, EBS, ELB, RDS, S3, Redshift, CloudWatch, Lambda.

• Expertise with Azure, and similar functionality services as above.

• Experience managing and supporting Docker, Kubernetes, Spark, Dask, Flask, CI/CD services.

• Experience with provisioning and configuration management tools; Puppet, Ansible, Chef, Terraform, etc.

• Strong Python, SQL skills a must

• Strong verbal & written communication skills and demonstrated ability of working with outside firms as a consultant

PREFERRED

• AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect).

• Experience developing data architecture, data instrumentation, database schemas (Graph, SQL, NoSQL), etc.

• Strong knowledge and understanding of CI/CD processes and tools (e.g., Jenkins).

• Master's or Ph.D degree in Physics, Math, Computer Science, Statistics, or related STEM field

BENEFITS

Base salary, bonus, medical coverage, 401k plan, paid time off (vacation, personal/sick, parental, etc.), flexible work-schedule, on-going sales & industry training, and other company-wide perks.

GROWTH

This person will have a complete view of data engineering and MLOps 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 engineer to grow into a manager role, develop professionally, work on many different projects per year, and help develop a cohesive team of engineers, consultants, and scientists to support AI development and services efforts.