Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines.  Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

You are a driven professional with a deep understanding of the machine learning tooling ecosystem and a strong passion for building scalable, robust systems. You thrive in a high-speed environment, enjoy solving complex problems, and have a keen eye for detail. Your expertise in AWS and MLOps, combined with your commitment to excellence in software practices, makes you an exceptional team player who can both lead and collaborate effectively. You are excited about the opportunity to work on groundbreaking projects and contribute to a team that's shaping the future of machine learning.

How will you contribute?

• Contribute to and oversee internal machine learning libraries to ensure scalability and efficiency across the team.
• Collaborate with Data Scientists and Research Engineers to evaluate, select, and integrate machine learning tools and frameworks.
• Manage and optimize AWS infrastructure to support scalable, high-performance machine learning applications.
• Ability to work across datasets in text, audio, images and multilingual.
• Enable highly parallelized experiments to scale efficiently across CPU and GPU resources.
• Design and build end-to-end pipelines for model training, evaluation, hyperparameter optimization, bias detection, and report generation.
• Maintain dataset management tools to power our data strategy.
• Incorporate and manage experiment tracking systems to support research and development.
• Ensure model building processes are enterprise-grade and repeatable.
• Work closely with production engineering teams on end-to-end MLOps and to establish effective contracts and connection points.
• Integrate and coordinate various components to build a cohesive, efficient machine learning infrastructure.

What will you bring?

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field.
• Extensive experience in building and managing machine learning infrastructure and tooling.
• Deep knowledge of MLOps best practices, including model deployment, monitoring, and scaling.
• Strong proficiency in AWS, with a proven track record of managing and optimizing cloud-based machine learning environments. Important services include EC2, Sagemaker, Batch and other ML-relevant services.
• Expertise in software engineering, including Python and other programming languages commonly used in machine learning.
• Excellent understanding of machine learning frameworks such as PyTorch, and Scikit-Learn, CUDA, Triton and TensorFlow.
• Experience with data management and pipeline orchestration tools (e.g., Airflow, Kubeflow).
• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Exceptional communication skills with a demonstrated ability to work effectively in a team-oriented environment.

What do we offer?

• Healthcare insurance — We provide medical, dental, and vision insurance, and a flexible spending account that allows you to set aside pre-tax dollars to pay for eligible out-of-pocket expenses.
• Personal time off — A healthy work-life balance is critical to your success at the office. Smarsh offers a “take-what-you-need” time off policy, as well as flexible work arrangements.
• 401K Match - Smarsh provides a 4% 401K match, for which employees are fully vested on day one.
• Sabbatical – The Smarsh sabbatical program provides a time to recharge, to study or simply a time to do something you are passionate about away from the workplace. Employees are eligible after six years of service.
• Recognition - We’re big on kudos for a job well done. Our employee-recognition program enables co-workers to nominate their peers who best embody our core values for recognition.

$170,000 - $220,000 a year

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.