Machine Learning Engineer 4 - Machine Learning Experiences (MLX)

Description

The company builds and ships AI and technology products that solve real business problems and customer needs, and works in a fast-moving, 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. You would help drive major AI changes and scale production models across the company.

Responsibilities

• Your work overlaps with Ops, Modeling and Data Engineering. You will perform one or more of the following ML engineering activities.
• Design, build and/or deliver ML models and components for real business problems, working with the Product and Data Science teams.
• Use your knowledge of modeling techniques and their pitfalls to guide infrastructure decisions, covering model and feature selection, data, training, hyperparameter tuning, dimensionality, bias and variance, and validation.
• Solve complex problems by writing and testing application code, building and validating ML models, and automating tests and deployments.
• Join a cross-functional Agile team to create and improve software for state-of-the-art big data and ML applications.
• Retrain, maintain and monitor models in production.
• Build or use cloud-based architectures, technologies and platforms to deliver optimized ML models at scale.
• Build optimized data pipelines that feed ML models.
• Apply continuous integration and deployment 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 best practices in Responsible and Explainable AI.
• Write code in Python, Scala or Java.

Requirements

• A 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 4 years of programming experience in Python, Java, Golang or C++.
• At least 4 years of machine learning experience with PyTorch or TensorFlow and libraries such as Pandas, NumPy and Scikit-learn.
• At least 4 years of experience running large-scale distributed systems such as Spark or Ray to prepare AI or ML data.
• At least 2 years of experience deploying and running ML solutions in production, operating production services in AWS, GCP or Azure, and managing large containerized ML systems with Kubernetes.
• Preferred: a master's or doctoral degree in Computer Science, Electrical Engineering, Mathematics or a related field.
• Preferred: 3+ years optimizing ML algorithms, configurations and infrastructure.
• Preferred: 3+ years following software development best practices such as source control, testing, code reviews and CI/CD.
• Preferred: 3+ 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: 3+ years working with supervised, semi-supervised, unsupervised and reinforcement learning, model types such as regression, classification and clustering, architectures such as RNNs, CNNs, LSTMs and Transformers, training concepts such as loss functions, hyperparameters and regularization, and evaluating accuracy and fixing underfitting and overfitting.
• Preferred: 3+ years designing, building and scaling production-ready data pipelines for training and evaluating ML models.
• Preferred: 1+ years as a technical lead developing ML solutions with industry best practices, patterns and automation.
• Preferred: you have authored or co-authored a paper on an ML technique, model or proof of concept.
• The company will not sponsor new applicants for work authorization or provide any immigration-related support for this role, including H-1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, O-1, or any other work authorization that requires employer immigration support.

Conditions

Full-time annual base salary ranges by location: Sales Territory and Richmond, VA: $179,400 to $204,700; Cambridge, MA and McLean, VA: $197,300 to $225,100; New York, NY and San Jose, CA: $215,200 to $245,600. Each range is for work in that location and reflects the company's pay at posting. Pay for other locations follows that location's range, and the exact salary appears in the offer letter. Part-time pay is prorated to agreed hours.

The role is eligible for performance-based incentive pay, which may include cash bonuses and/or long-term incentives, and may be discretionary or non-discretionary depending on the plan.

Applications will be accepted for at least 5 business days.

No agencies. The company is an equal opportunity employer and does not tolerate discrimination; it considers applicants with criminal histories in line with applicable law.

Benefits

• A broad package of health, financial and other benefits, with eligibility depending on full- or part-time status, exempt or non-exempt status and management level. Details are on the company careers site.
• Performance-based incentive pay as described in conditions.