Machine Learning Engineer 5 (Senior Manager, IC)

Description

The company builds AI and technology products and solves complex business problems in a fast-paced, collaborative, iterative setting.

The team is looking for machine learning engineers who enjoy working with cutting-edge open source frameworks, advanced algorithms and emerging technologies.

In this role you will help drive major AI transformation and move production models to scale across the company.

Responsibilities

• Work across Ops, modeling and data engineering, taking on one or more ML engineering activities.
• Design, build and deliver ML models and components for real business problems, working with Product and Data Science teams.
• Build and scale large multi-tenant platforms that run ML training and serving at high volume.
• Make infrastructure decisions based on your understanding of modeling issues such as model, data and feature choice, training, hyperparameter tuning, dimensionality, bias/variance and validation.
• Write and test application code, develop and validate ML models, and automate testing and deployment.
• Work in a cross-functional Agile team to create and improve software for big data and ML applications.
• Retrain, maintain and monitor models in production.
• Use or build cloud-based architectures and platforms to deliver optimized ML models at scale.
• Build optimized data pipelines that feed ML models.
• Apply CI/CD practices, including test automation and monitoring, to deploy ML models and application code reliably.
• Keep code well managed to reduce vulnerabilities, keep models governed from a risk standpoint, and follow Responsible and Explainable AI practices.
• Write code in Python, Scala or Java.

Requirements

• Bachelor's degree or higher in Computer Science, Machine Learning or a related quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics or Engineering.
• At least 6 years of programming experience in Python, Java, Golang or C++.
• At least 6 years of machine learning experience with PyTorch or TensorFlow and libraries such as Pandas, NumPy and Scikit-learn.
• At least 6 years of working with large scale distributed systems such as Spark or Ray to prepare AI or ML data.
• At least 4 years of deploying and running ML solutions in production and operating cloud services on AWS, GCP or Azure, including Kubernetes for large containerized ML systems.
• Preferred: Master's or doctoral degree in Computer Science, Electrical Engineering, Mathematics or a related field.
• Preferred: 5+ years optimizing ML algorithms, configurations and infrastructure.
• Preferred: 5+ years applying software development best practices such as source control, testing, code reviews and CI/CD.
• Preferred: 5+ years building resilient software with pre-production testing, advanced deployment methods (one-box, blue/green, gradual dial-up), monitoring, alarms and incident response plans.
• Preferred: 5+ years using ML techniques (supervised, semi-supervised, unsupervised and reinforcement learning), model types (regression, classification, clustering), architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss functions, hyperparameters, regularization), and diagnosing issues such as underfitting and overfitting.
• Preferred: 5+ years designing, implementing and scaling production-ready data pipelines for ML training and evaluation.
• Preferred: ML industry impact through conference talks, papers, blog posts, open source contributions or patents.
• Preferred: Ability to explain complex technical and ML concepts clearly to varied audiences.

Conditions

The company will consider sponsoring a new qualified applicant for employment authorization for this position.

Salary ranges by location for full-time roles: Cambridge, MA and McLean, VA: $229,900 - $262,400; New York, NY, San Francisco, CA and San Jose, CA: $250,800 - $286,200. Part-time pay is prorated to the agreed hours. Candidates hired elsewhere get the range for their location, with the exact salary stated in the offer letter.

Applications will be accepted for at least 5 business days.

No agencies. The company is an equal opportunity employer and considers applicants with criminal histories in line with applicable law.

Benefits

• Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives, either discretionary or non-discretionary depending on the plan.
• Health, financial and other benefits, with eligibility depending on full- or part-time status, exempt or non-exempt status and management level.