ZipRecruiter

Log In

1

Compression Engineer Jobs in New York (NOW HIRING)

Meta

Research Engineer, Monetization AI

New York, NY

$183K/yr

Research Engineer, Monetization AI Responsibilities: * Develop and implement large-scale model ... compression, and resource-efficient AI, to drive performance improvements and efficiency gains

Beacon Software Inc

Forward Deployed Engineer

New York, NY · On-site

$141K/yr

The 11th deployment in a home-services SaaS should be 10x faster than the 1st, and that compression is your job as much as the engineers building the platform. * Carry the GM relationship. You are ...

NAVA Software Solutions

ETL Developer

Jersey City, NJ · On-site

$53 - $69.50/hr

NAVA Software solutions is looking for a ETL Developer Details: ETL Developer Location: Jersey city ... compression, Direct path loads etc. and that maximizes re-usable components and services that ...

Palantir

Software Engineer - Apollo Systems

Manhattan, NY · On-site

$145 - $200/hr

As a Software Engineer on the Apollo team, you'll build and operate a large‑scale distributed ... compression infrastructure tailored to Palantir's deployment models. You'll also build and optimize ...

previous page

Showing results 41-60

All JobsCompression Engineer JobsCompression Engineer Jobs in New York

Compression Engineer information

What is the difference between Compression Engineer vs Mechanical Engineer?

AspectCompression EngineerMechanical Engineer
Required CredentialsBachelor's in Mechanical, Aerospace, or related fields; certifications like PE or ASME often preferredBachelor's or higher in Mechanical Engineering; PE license beneficial
Work EnvironmentDesign and testing of compression systems, working in labs or manufacturing settingsDesign, analysis, and manufacturing of mechanical systems across various industries
Industry UsageOil & gas, HVAC, power generation, manufacturingAutomotive, aerospace, manufacturing, energy
Common Search/ComparisonYesYes

While both roles require a strong background in mechanical principles, a Compression Engineer specializes in designing and testing compression systems like turbines or compressors, often within energy or manufacturing sectors. Mechanical Engineers have a broader scope, working on various mechanical systems across multiple industries. The roles overlap in skills and credentials but differ in focus and application.

What does a compression engineer do?

A compression engineer designs, analyzes, and improves compression systems used in various industries such as oil and gas, manufacturing, and power generation. They work with equipment like compressors, turbines, and valves, often using simulation tools and adhering to safety standards. Their role involves troubleshooting, optimizing performance, and ensuring reliable operation of compression machinery.

What are popular job titles related to Compression Engineer jobs in New York?

For Compression Engineer jobs in New York, the most frequently searched job titles are:

What job categories do people searching Compression Engineer jobs in New York look for?

The top searched job categories for Compression Engineer jobs in New York are:

What cities in New York are hiring for Compression Engineer jobs?

Cities in New York with the most Compression Engineer job openings:

Compression Engineer jobs near you
Infographic showing various Compression Engineer job openings in New York as of August 2026, with employment types broken down into 87% Full Time, and 13% Contract. Highlights an 85% In-person, and 15% Remote job distribution.

Principal Software Engineer - AI Foundations

JPMorgan Chase & Co.

Jersey City, NJ • On-site

$204K - $285K/yr

Full-time

Medical, Retirement

Re-posted 22 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

77th of 175 rated banks

Job description


As a Principal Software Engineer at JPMorganChase within the Chief Data and Analytics Office (CDAO), you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way.
In this role, you will lead the design and evolution of the firm's GenAI serving platform, focused on high-performance LLM inference, intelligent model routing, and GPU efficiency, to deliver reliable, cost-effective AI capabilities at enterprise scale. Leveraging your advanced technical capabilities and collaborating with colleagues across the organization you will drive best-in-class outcomes across various technologies to support one or more of the firm's portfolios. Influence leaders and senior stakeholders across business, product, and technology to drive alignment and outcomes; foster a culture of diversity, opportunity, inclusion, and respect.
Job Responsibilities
  • Design, build, and operate a high-throughput, low-latency LLM serving platform (batching, scheduling, caching, streaming responses, multi-tenancy, and autoscaling) across GPU/CPU fleets.
  • Build and evolve a GenAI Gateway / inference API layer (authentication, authorization, quota/rate limiting, routing, request shaping, policy enforcement hooks, and standardized observability) to support diverse application workloads.
  • Develop and optimize "open routing" / intelligent model routing across multiple model backends (open-source and vendor models), balancing quality, latency, reliability, and cost with configurable policies and guardrails.
  • Drive GPU serving optimization: kernel-level performance tuning where needed; model compilation/acceleration (e.g., TensorRT-style approaches), efficient memory management, KV-cache strategies, and throughput tuning (prefill vs. decode optimization).
  • Implement quantization and compression strategies (e.g., INT8/INT4, weight-only quantization), including evaluation-driven selection and safe rollout practices that preserve quality and reduce cost/latency.
  • Design and implement disaggregated serving patterns (e.g., separating prefill/decode, KV-cache offload, tiered serving) and distributed inference architectures to improve utilization and tail latency.
  • Develop secure, high-quality production code; review, debug, and improve code written by others; create durable, reusable frameworks and platform components leveraged across teams, aligned to modern product development methodologies.
  • Own and support SDK and service integrations, ensuring reliability, performance, and maintainability.
  • Establish SLOs/SLAs for inference services and build operational excellence (load testing, capacity planning, incident response playbooks, regression detection, and continuous performance benchmarking); build robust performance and cost observability (latency histograms, token throughput, GPU utilization, memory fragmentation, cache hit rates, per-tenant cost attribution) and automate remediation of recurring issues.
  • Architect and govern agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams.
  • Apply knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale .

Required qualifications, capabilities, and skills
  • Formal training or certification on software engineering concepts with 7+ years applied experience including hands-on delivery of system design, application development, testing, and operational stability for large-scale platforms and services.
  • Expert proficiency in one or more programming languages (e.g., Python, Java, Scala, Go) with strong code quality, testing, and debugging practices.
  • Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.
  • Proven experience designing and operating high-scale inference and distributed systems (multi-tenant services, backpressure, load shedding, rate limiting, request prioritization, and tail-latency reduction).
  • Strong understanding of GPU-serving fundamentals (compute/memory trade-offs, batching, concurrency, network bottlenecks, and performance profiling) and experience improving efficiency/utilization in production.
  • Experience with model serving stacks and patterns (model registries/artifacts, rollout strategies, canaries, A/B, shadow traffic) and performance benchmarking methodologies.
  • Practical cloud-native experience (containers, orchestration, IaC, observability) and experience operating production systems with clear SLOs.
  • Experience applying new methods to solve complex technology problems across one or more technical disciplines (platform engineering, ML systems, data engineering, distributed systems).
  • Strong communication skills: able to present to and influence senior leaders/executives, translating complex technical topics into clear decisions and trade-offs.
  • Strong understanding of business outcomes and product delivery, and ability to align platform roadmaps to measurable impact.

Preferred qualifications, capabilities, and skills
  • Deep experience with LLM inference optimization techniques (e.g., speculative decoding, KV-cache management, paged attention-style approaches, optimized sampling, continuous batching).
  • Practical experience with quantization and compression toolchains (evaluation, calibration, regression testing, production rollout) and understanding of quality/performance trade-offs.
  • Experience designing disaggregated serving architectures (prefill/decode separation, cache offload, distributed inference) and operating them at scale.
  • Experience building model routing and governance layers (policy-based routing, fallback strategies, circuit breakers, per-tenant controls, cost-aware routing).
  • Strong performance engineering background (profiling, flame graphs, GPU profiling, bottleneck analysis) and production tuning under real workload constraints.
  • Experience with multi-tenant platforms, reusable frameworks, and developer self-service capabilities at enterprise scale.
  • Strong security-by-design experience for ML/LLM systems (secrets, access control, data handling, supply chain controls) and resiliency engineering.

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply