Hybrid Senior AI/ML Engineer

at skillventory - A Leading Talent Research Firm

• Job title: Senior AI/ML Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: $97,000 - $185,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Distributed Systems, Docker, Groovy, Java, Jenkins, Linux, Numpy, Pandas, Python, Scikit-Learn, Tensorflow, Terraform
• Location requirements: Hybrid, Westlake, United States

About the role

• Senior ML Ops Engineer creating frameworks to support ML infrastructure and collaborate with data scientists. Focus on AI/ML solutions in financial services, enhancing customer experiences.

Responsibilities

• As a Sr Machine Learning Ops Engineer within the Enterprise Data Science Platform team, you will create frameworks to support large-scale ML infrastructure and pipelines, including tools for the containerization and deployment of ML models
• Collaborating with Data Scientists, you will develop advanced analytics and machine learning platforms to enable the prediction and optimization of models
• You will extend existing ML platforms for scaling model training and deployment, and partner with various business and engineering teams to drive the adoption and integration of model outputs
• This role is essential in leveraging Data Science to deliver exceptional customer experiences in financial services
• Responsible for building advanced cloud and software solutions in collaboration with Data Scientists to support packaging, deployment, and scaling of AI/ML Models in production

Requirements

• Has bachelor’s or master’s Degree in a technology related field (e.g. Computer Science, Engineering, etc.)
• Proven experience in building cloud-native applications using a range of AWS services, including but not limited to SageMaker AI, Bedrock, S3, CloudFormation (CFT), SNS, SQS, Lambda, AWS Batch, Step Functions, EventBridge, and CloudWatch
• Familiarity with both Azure Cognitive Services, particularly for deploying OpenAI models, and Google Compute Vertex is beneficial
• Strong experience with CI/CD tools, particularly Jenkins, for automating and streamlining the software development pipeline
• Proficient in using version control systems like Git for effective code management and collaboration
• Hands-on experience with containerization technologies such as Docker for building and deploying applications
• Expertise in infrastructure as code (IaC) services, including AWS CloudFormation and tools like Terraform or OpenTofu, for managing and provisioning cloud resources
• Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies
• 5+ years of proven experience in developing and implementing Python-based cloud applications and/or machine learning solutions
• 1+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker
• Proficiency in Python software development with strong experience in its ML ecosystem (numpy, pandas, sklearn, tensorflow, etc.), along with solid skills in Linux scripting
• Ability to design and implement software using both object-oriented and functional programming paradigms
• Basic knowledge of Java and Groovy is a plus
• Strong knowledge of developing highly scalable distributed systems using Open-source technologies
• Solid experience in Agile methodologies (Kanban and SCRUM)

Benefits

• comprehensive health care coverage and emotional well-being support
• market-leading retirement
• generous paid time off and parental leave
• charitable giving employee match program
• educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career