Machine Learning Engineer

Ventera’s mission is to be a growing business technology consulting firm recognized for earning the loyalty of customers and employees by committing to their success. Ventera delivers innovative business and technology solutions to unique customer challenges, to help our clients achieve meaningful results. Our team brings expertise and serves as a trusted advisor to our clients in the areas of Management Consulting, Software Engineering, and Data Solutions. We strive to make Ventera a fun place to work, as well as a place where you will want to stay and build your professional career. We are a Washington Post Top 20 Workplaces Award Winner. Come Join Us!!

We are seeking a skilled and motivated Senior Machine Learning Engineer to join our team. As a Senior Machine Learning Engineer at Ventera, you will have the opportunity to work on cutting-edge projects that leverage the AWS Machine Learning ecosystem (SageMaker, EC2/ECS, S3 buckets, etc.). Your primary responsibilities will involve developing, deploying, and maintaining dozens of machine learning models in production using AWS services, as well as optimizing data pipelines for maximum efficiency. The current model development focus is on Anomaly Detection Timeseries prediction, with more added projects in the future.

Key Responsibilities:

Collaborate with cross-functional teams to understand business needs and develop machine learning solutions.
Utilize AWS SageMaker, EC2/ECS, AWS SDK, S3 buckets and the rest of the AWS ML ecosystem to build, train and deploy machine learning models at scale.
Develop and maintain clean, efficient, and well-documented Python code following best coding practices.
Knowledge of deep learning frameworks such as PyTorch/Tensorflow, and other ML packaged libraries to design and implement machine learning algorithms (i.e. DARTS for timeseries, PyCaret for tree-based solutions, etc.).
Create and analyze datasets, conduct experiments, and fine-tune models to achieve optimal performance.
Use SageMaker Notebooks and other relevant tools for data exploration, visualization, and model evaluation.
Stay up to date with the latest advancements in machine learning and AWS services to drive innovation within the team.
Qualifications:

Bachelors or Masters degree in Computer Science, Machine Learning, or a related field.
5 or more years of hands-on experience as a Machine Learning Engineer. 15 years IT experience.
Proficiency in Python and strong coding skills with a focus on clean and efficient code.
Experience with AWS services, particularly SageMaker, EC2/ECS, AWS SDK, and S3 buckets.
Experience with fine-tuning and deploying large language models, RAG and multi-agent LLMs.
Experience with monitoring and evaluating large language models.
Familiarity with AIML frameworks such as PyTorch/Tensorflow/other open-sourced libraries.
Strong analytical and problem-solving skills.
Excellent communication and teamwork abilities.
Great all around get it done attitude. Although we work remotely, the team here has a great culture, and we are looking to maintain that great team!
Additional Nice to Have Qualifications:

Previous experience with Docker and containerization within AWS.
Knowledge of serverless computing using AWS Lambda.
Understanding of MLOps and DevOps practices, experience with building data pipelines.
MLflow + Evidently or similar technologies.
Previous experience developing front ends for data science POCs.
Experience with version control systems like Git.
Experience with multivariate time series forecasting.
Experience in an Agile coding environment is a bonus (though not required, that can be picked up quickly).
Perks of working at Ventera

Inclusive culture, providing a great work/life balance
Flexible work schedules
Medical, dental & vision coverage for employee
5 weeks of PTO & unlimited sick leave
Career coach development program
Educational benefits for training, conferences, certifications, tuition etc.
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.