Applied Machine Learning Engineer

The Role

Smile Identity is on the lookout for a seasoned Applied Machine Learning Engineer to elevate our Machine Learning systems to new heights. Ideal candidates will have a robust foundation in statistics, programming, and a proven track record in machine learning roles, specifically within the realms of facial biometrics, document fraud detection, and related fields. Your mission will involve refining our AI's predictive capabilities through rigorous evaluation and enhancement of existing ML processes. Joining us means contributing significantly to a growth-stage company, directly influencing the success of our Computer Vision/Machine Learning department, and by extension, the broader organizational objectives. This role offers a direct line of report to the Head of Artificial Intelligence.

Primary Responsibilities

• Lead the development and optimization of deep learning models, focusing on biometric authentication, face detection, and antispoofing technologies.
• Oversee the creation, cleaning, and management of datasets to train and test machine learning models, ensuring data quality and representativeness for real-world application.
• Conduct thorough evaluations of machine learning models to ensure their readiness for deployment, with a particular emphasis on performance, efficiency, and scalability.
• Implement and advocate for data governance best practices, emphasizing ethical considerations and privacy in data handling and machine learning processes.

What We’re Looking For

• A minimum of 5 years of professional experience in software engineering, applied algorithm development, and machine learning, with a strong emphasis on facial biometrics and document fraud detection.
• Advanced degree in Computer Science, Mathematics, Physics, Engineering, or a related field is preferred.
• Expertise in Python, Linux, AWS (S3, EC2, RDS), Git, Docker, SQL, Numpy, Tensorflow, and/or PyTorch.
• Demonstrated proficiency in exploratory data analysis using Jupyter Notebooks or VScode.
• Solid experience in data governance strategies, including feature stores and model registries.
• Background in a startup environment, working within agile, team-based methodologies.
• Experience working with remote, distributed teams is highly valued.
• Proven ability to manage multiple projects autonomously in a dynamic, digital, and remote business setting.
• Desirable skills include C++, OpenCV, CI/CD principles, streaming architecture, serverless concepts, development of data/ML model regression tests, computer vision pipelines, container orchestration (e.g., Kubernetes, ECS), ML for mobile/IoT, model compression techniques, embeddings and vector search, and incremental and active learning methods.
• Proficiency with Google Suite or related software is expected.

Compensation

• A competitive compensation package with stock options.
• Comprehensive healthcare benefits.
• Flexibility with a remote working arrangement.
• An opportunity to be part of a purpose-driven technology company at a pivotal growth stage.

By applying for the role you consent to the GDPR Statement