Machine Learning Engineer II

Machine Learning Engineer II

About the Role

As a Machine Learning Engineer II, you will lead the productization of AI/ML research pipelines, transforming proof-of-concept models into robust, scalable, and production-grade systems. You will serve as the technical owner of ML pipeline productization efforts, bridging the gap between research and production by collaborating closely with AI scientists and software engineers. Working within Sorenson's AI Lab, you will ensure that our ML systems are performant, reliable, secure, and maintainable at scale.

Essential Duties and Responsibilities

• Own end-to-end productization of ML research pipelines, from proof-of-concept to production-grade systems, ensuring functional parity, reliability, and scalability.
• Design and implement production ML inference pipelines, including preprocessing, model serving, and postprocessing stages, with a focus on low latency and throughput.
• Architect scalable microservice-based or modular ML systems, making deliberate decisions around system design (e.g., monolith vs. microservices, synchronous vs. asynchronous processing).
• Build and maintain APIs and backend services (REST, gRPC, WebSocket) to support real-time and batch ML inference at scale.
• Containerize ML model pipelines using Docker and deploy them on cloud platforms (AWS preferred), leveraging orchestration tools such as Kubernetes or ECS.
• Implement MLOps best practices including CI/CD pipelines, automated testing, model versioning, and reproducible build environments.
• Develop robust monitoring and observability tooling to track system health, model performance, latency, and data drift in production.
• Ensure systems are secure and compliant, including model encryption at rest, TLS/mTLS traffic encryption, PII controls, and network egress restrictions.
• Collaborate with research scientists to understand model requirements, manage dependencies, and coordinate handoffs from research to production.
• Optimize ML model pipelines for inference efficiency using techniques such as quantization, batching, and hardware acceleration (GPU/CPU).
• Lead and mentor junior engineers on the team, driving technical decisions and code quality standards.
• Document system architecture, software design decisions, and operational runbooks to ensure maintainability and knowledge transfer.
• Other duties as assigned.

Education

• Minimum: Bachelor's Degree in Computer Science, Computer Engineering, Mathematics, or a related field.
• Preferred: Master's or PhD in Computer Science, Machine Learning, or a related technical field.

Experience

5 years of experience in software engineering with a focus on ML systems, MLOps, or production AI pipelines. A Master's degree may be considered equivalent to 2 years of experience. A PhD may be considered equivalent to 3 years of experience.

Knowledge, Skills, and Abilities

• Strong proficiency in Python and experience with ML frameworks such as PyTorch and TensorFlow.
• Demonstrated experience deploying and serving ML models in production environments, including familiarity with model serving runtimes such as Triton Inference Server, TorchServe, vLLM or equivalent.
• Experience containerizing and orchestrating ML workloads using Docker and Kubernetes (or AWS ECS/EKS).
• Hands-on experience with cloud platforms, preferably AWS, including services such as ECS, EKS, S3, ECR, CloudWatch, and Lambda.
• Strong understanding of software engineering principles including modular design, testability, and CI/CD pipeline development (e.g., GitHub Actions).
• Experience building APIs and backend services using REST, gRPC, or WebSocket protocols for real-time or streaming applications.
• Familiarity with MLOps tooling and practices: experiment tracking, model versioning, pipeline orchestration (e.g., MLflow, DVC, Airflow, or equivalent).
• Experience with monitoring and observability tools such as AWS CloudWatch, Datadog, Prometheus, or Dynatrace.
• Understanding of security best practices in ML systems: model encryption at rest, TLS traffic encryption, PII handling, and network access controls.
• Experience with model optimization techniques for inference efficiency, such as quantization, pruning, batching, or ONNX export.
• Ability to write comprehensive unit, integration, and load tests for ML-integrated systems.
• Excellent communication and collaboration skills, with experience working across research and engineering teams.
• Experience working with video, audio, or multimodal ML pipelines is a plus.
• Experience with Infrastructure as Code tools such as Terraform is a plus.
• Professional attitude, team player, good interpersonal communication skills and able to work across company departments.

Supervisory Responsibility

This position has no direct supervisory responsibilities but does serve as a coach and mentor for other positions in the department.

Travel Requirements

Less than 25%

Full-Time Benefits

• Paid Vacation Time and Paid Sick Time and Paid Holidays
• 401k 6% match with immediate vesting
• Nationwide Medical Insurance plans and coverage (Medical, Dental/Orthodontia, Vision)
• TeleDoc
• HSA company match
• 3 Medical plan options including a Low Deductible PPO Medical Plan Offering
• Employee Assistance Program
• Engaged Employee Resource Groups
• Outstanding Learning and Career Development Opportunities

Compensation

Pay Range: Actual pay may vary up or down depending on job-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for incentive compensation.

Employment Requirements

Applicants must be legally eligible to work in the United States to be considered. Visa sponsorship is not available for this role.

About Sorenson Communications

Mission: Harnessing the power of language, we connect diverse people and enrich the human experience.

Vision: To provide global language services that expand opportunities, nurture belonging, and empower the world to connect beyond words.

As one of the world's leading language services providers, Sorenson combines patented technology with human-centric solutions. We strive to increase accessibility and inclusion through communication solutions for all: call captioning and video relay services, over-video and in-person sign language and spoken language interpreting, translation, real-time captioning, and post-production language services. Sorenson's impact vision and plan extends to enhancing generational wealth and inclusive workplaces for our employees and the communities we serve.

We achieve great things together working "The Sorenson Way" with our employee values: Customer First, Can-Do Attitude, Collective Action, Growth Mindset, Ownership, and Connect Direct.

Equal Employment Opportunity

Sorenson Communications is an Equal Opportunity, Affirmative Action Employer.