AuthenticID is solving the biggest business issue in the world today: Identity-driven Fraud.
Our dynamic, fast growth culture is mission-focused on stopping the bad guys to protect the good guys. Our efforts not only save our customers billions of dollars, but also impede the dehumanizing activities of organized crime, related to drug and human trafficking. What we do matters. It’s more than a job, it’s a movement on the frontlines of the digital transformation that impacts almost everybody in today’s world.
The Senior ML Engineer reports to the ML Engineering Manager and will be part of the Research and Development team. This role leads the development of highly scalable production ML models and workflows. By leveraging cloud native technologies and MLOps best practices this role helps transition prototypes from the Research team to high performance ML workflow services in production. The role is a key contributor to the development of our AutoML strategy that will be used for training, development, deployment, and maintenance of our models. This role also works closely with the Data Scientists to ensure accurate delivery of ML models and to provide the architecture required to advance the research.
Top 3 key outcomes in the first year include:
- Technical delivery – Develop production-grade deployable artifacts from model prototypes. Facilitate model development life cycle and production delivery using Amazon SageMaker ecosystem to create a repeatable and automated process for training, evaluating, and deploying ML models.
- Speed increase – Employ managed services to reduce the time to value for on-demand releases of new models as well as for systematic updates to the existing models using a feedback loop.
- Technical leadership – Advocate best practices in ML engineering and operations. Provide technical mentorship to junior team members, and contribute to the design of the ML platform architecture.
- Proficiency in designing and implementing scalable production ML workflows in the cloud
- Experience with at least one ML framework such as Pytorch, TensorFlow, or Scikit-learn
- Knowledge of machine learning and computer vision fundamental concepts
- Excellent software engineering skills and the ability to provide technical mentorship and guidance
- $100M and upward company scale up experience
- AuthenticID company values and culture fit
- STEM Master’s Degree or equivalent
- Background check and drug screen required
- 4+ years of experience in design and development of scalable systems used for running ML workloads, distributed model training, hyperparameter tuning, and real-time inference
- 6+ years of Software Engineering experience
- 3+ years of cloud experience, preferably AWS SageMaker ecosystem
- Competitive salary and option grants
- Flexible hours and recovery days
- Medical & Dental Insurance, and Life
- Paid Parental leave
- Once-in-a-lifetime experience taking a startup into scale mode, working directly with experienced founders and a diverse, fun-loving and hardworking team
LOCATION: Seattle, WA region or United States Remote