Junior Machine Learning Engineer

Fama is the innovator in online screening that makes hiring great people easy. Combining Fama’s groundbreaking AI technology and ability to integrate across the HR Tech stack, the solution compliantly searches over 10,000 online public sources to help companies avoid workplace misconduct, prevent costly legal action and ultimately, make better decisions. By modernizing candidate screening and due diligence, Fama helps organizations, agencies, and investors improve the quality of hires, make the most of each investment and build successful businesses.

Headquartered in Los Angeles, CA, Fama has raised over $30M and is backed by some of the world’s leading venture capitalists and institutional investors. We’re FCRA, EEOC, and SOC2 compliant, and integrate with major HRIS, ATS, and background check solutions. To learn more, visit Fama.io.

Position Overview:
Fama is seeking a Junior Machine Learning Engineer to join our Data Science and Analytics team to advance the next generation of our AI/ML infrastructure. The successful candidate will spearhead the deployment, tracking, and CI/CD around our models so that we can smoothly create new and push changes to existing ML models. The junior ML Engineer will also be responsible for model tuning, testing and monitoring, and performance optimization.

You will work closely with a distributed Data Science and Analytics team, Product Engineering partners, and other stakeholders to develop new models for our SaaS product lines. Our AI/ML models are at the core of our products and our team seeks innovative individuals who strive to build industry-leading products.

Responsibilities

• Create and maintain MLOps pipelines that support automatic retraining and deployment of our models.
• Establish version control and best practice CI/CD around model deployment.
• Deploy and optimize a wide range of ML models created by our data scientists in the cloud.

Qualifications

• Experience in DevOps and/or MLOps establishing CI/CD for large machine learning models
• *Strong bonus experience: 1 - 2 years of deep learning/computer vision/natural language processing/machine learning/computer science with equivalent industry experience (or, in exceptional cases, BS with a proven track record of relevant industry or transferrable experiences).
• Proficiency in common machine learning packages such as Scikit-learn, TensorFlow, PyTorch, etc.
• Proficiency with MLOps frameworks such as MLFlow, Kubeflow, TFX, Airflow, etc.
• Familiarity with algorithms, such as clustering, forecasting, anomaly detection, classification, and graph networks.
• Comfortable working with cloud Infrastructure (AWS, GCP, Azure, etc.)

We believe that becoming an increasingly diverse, equitable, and inclusive workplace makes us a more successful and resilient organization. We embrace equal opportunity for all applicants and seek to foster and preserve a culture of belonging for our employees. We recognize and appreciate that the more inclusive we are, the better we will function as a team. We are committed to providing equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, gender identity, gender expression, age, marital or family status, disability, military veteran status, and any other status or background.