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Remote Gas Engine Performance Engineer Jobs in Massachusetts

Leidos

Civil/Structural Engineer

Framingham, MA · On-site +1

... performance-based solutions. Our services include engineering, planning, project management ... Fully remote would be considered on a case-by-case basis. There is an identical senior level ...

Databento

Software Engineer (C++/Rust)

Boston, MA · On-site +1

Good communication skills and work ethic for a remote workplace. * An interest in low-level optimization and performance engineering. * An interest in financial data or algorithmic trading. Notice ...

Databento

Good communication skills and work ethic for a remote workplace. * An interest in low-level optimization and performance engineering. * An interest in financial data or algorithmic trading. Notice ...

Databento

Good communication skills and work ethic for a remote workplace. * An interest in low-level optimization and performance engineering. * An interest in financial data or algorithmic trading. Notice ...

Databento

Good communication skills and work ethic for a remote workplace. * An interest in low-level optimization and performance engineering. * An interest in financial data or algorithmic trading. Notice ...

Travelers

Senior Manager, SEO & GEO

Boston, MA · Remote

$114K - $189K/yr

... performance-based cash incentive awards. Salary Range $114,700.00 - $189,200.00 Target Openings 1 ... Engineering teams to translate strategy into action, establishing EEAT practices throughout ...

Simply Business

Senior Manager, SEO & GEO

Boston, MA · Remote

$114K - $189K/yr

... performance-based cash incentive awards. Salary Range $114,700.00 - $189,200.00 Target Openings 1 ... Engineering teams to translate strategy into action, establishing EEAT practices throughout ...

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All JobsGas Engine Performance Engineer JobsRemote Gas Engine Performance Engineer JobsRemote Gas Engine Performance Engineer Jobs in Massachusetts

Remote Gas Engine Performance Engineer information

What is the difference between Remote Gas Engine Performance Engineer vs Remote Gas System Analyst?

AspectRemote Gas Engine Performance EngineerRemote Gas System Analyst
Required CredentialsBachelor's in Mechanical or Electrical Engineering, certifications in engine testingBachelor's in Mechanical, Chemical, or Petroleum Engineering, certifications in gas systems analysis
Work EnvironmentDesign labs, field testing sites, remote monitoringData analysis, system modeling, remote diagnostics
Employer & Industry UsageEnergy companies, engine manufacturers, research institutionsOil & gas companies, utilities, engineering consultancies

The Remote Gas Engine Performance Engineer focuses on optimizing engine performance through testing and analysis, often working directly with engines. In contrast, the Remote Gas System Analyst specializes in analyzing and modeling gas systems remotely to improve efficiency and safety. Both roles require technical expertise but differ in their focus areas within the gas industry.

How does a remote gas engine performance engineer typically collaborate with on-site teams to troubleshoot performance issues?

As a Remote Gas Engine Performance Engineer, you will regularly coordinate with on-site maintenance and operations teams using virtual tools such as video calls, remote monitoring systems, and shared diagnostic platforms. You may analyze real-time engine data remotely, guide on-site staff through troubleshooting steps, and provide recommendations for optimizing performance or resolving faults. Effective communication skills and the ability to interpret data while not being physically present are essential in ensuring smooth collaboration and timely problem resolution.

What are the key skills and qualifications needed to thrive as a remote gas engine performance engineer, and why are they important?

To thrive as a Remote Gas Engine Performance Engineer, you need expertise in mechanical or automotive engineering, strong analytical skills, and a relevant engineering degree. Familiarity with engine diagnostic tools, performance monitoring software, and industry-standard modeling systems like MATLAB or GT-Power is typically required. Excellent problem-solving abilities, communication, and the capacity to work independently are standout soft skills in this remote role. These competencies are essential for accurately assessing engine performance, optimizing operations, and collaborating effectively with distributed teams.

What does a remote gas engine performance engineer do?

A Remote Gas Engine Performance Engineer is responsible for monitoring, analyzing, and optimizing the performance of gas engines from a remote location. They use specialized software and data analytics to assess engine efficiency, diagnose issues, and recommend improvements to ensure optimal operation. Their work often involves collaborating with on-site engineers, providing technical support, and generating performance reports to help minimize downtime and maximize engine productivity.
What are popular job titles related to Remote Gas Engine Performance Engineer jobs in Massachusetts? For Remote Gas Engine Performance Engineer jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Remote Gas Engine Performance Engineer jobs in Massachusetts look for? The top searched job categories for Remote Gas Engine Performance Engineer jobs in Massachusetts are:
What cities in Massachusetts are hiring for Remote Gas Engine Performance Engineer jobs? Cities in Massachusetts with the most Remote Gas Engine Performance Engineer job openings:
Remote Gas Engine Performance Engineer jobs near you
Infographic showing various Remote Gas Engine Performance Engineer job openings in Massachusetts as of June 2026, with employment types broken down into 10% As Needed, 80% Full Time, and 10% Contract. Highlights an 100% Remote job distribution.

Senior Engineer, Inference Data Plane

DigitalOcean

Boston, MA • Remote

$139K - $174K/yr

Full-time

Posted 15 days ago

Job description

DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Data Plane team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. You will work at the intersection of distributed systems and specialized AI hardware to ensure our customers can deploy and scale their models with industry-leading performance and reliability. This is a hands-on role, requiring you to be able to develop high quality software while availing of all the productivity boosts granted by the latest AI coding agents. 

What You'll Do:
  • Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models.
  • System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards.
  • Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing.
  • Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs.
  • Distributed Serving at Scale: Build on Kubernetes-native distributed inference frameworks like llm-d (or alternatives such as NVIDIA Dynamo, Ray Serve, KServe) to deliver prefill/decode disaggregation, KV-cache-aware routing, tiered prefix caching, and wide expert parallelism for MoE models.
  • Flow Control & Load Balancing: Solve the distributed-systems problems unique to LLM serving - inference-aware load balancing on queue depth, cache locality, and predicted latency; flow control and fairness across tenants; autoscaling inference pools; and moving gigabytes of KV-cache between prefill and decode instances with negligible overhead.
  • Open Source Contributions: Contribute upstream to llm-d, vLLM, and the inference gateway ecosystem, and represent DigitalOcean in these communities.
  • Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement.
  • Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health.
What You'll Bring to DigitalOcean:
  • AI/ML Domain Knowledge: Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or TensorRT.
  • Inference Frameworks: Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve.
  • Inference Engine Depth: Hands-on experience with vLLM or alternatives (SGLang, TensorRT-LLM, TGI, Modular MAX), including internals like continuous batching, paged attention, and prefix caching.
  • Distributed Inference Fluency: Understanding of why cluster-scale serving is hard: KV-cache locality is partitioned across workers, naive round-robin routing destroys cache hit rates and tail latency, and disaggregated prefill/decode requires fast cross-pod KV transfer (e.g., NIXL).
  • Upstream Track Record: Merged contributions to vLLM, llm-d, SGLang, or similar projects strongly preferred.
  • Architecture Proficiency: Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization).
  • Software Engineering: Expert-level proficiency in GoLang or Python and familiarity with gRPC.
  • Cloud Operations: Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean.
  • Open Source Mindset: Experience integrating and building with open-source software.
Compensation Range: 
  • $139,200 - $174,000

*This is a remote role

JR: 2026-7624

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