ML Engineer Jobs in Pennsylvania
ML Engineer jobs in Pennsylvania are in strong demand, with active hiring concentrated in fintech, healthcare informatics, defense contracting, and academic research across experience levels from entry-level to principal engineer. Philadelphia and Pittsburgh lead the market, with Malvern and King of Prussia adding significant suburban volume, and established employers like Comcast, Carnegie Mellon University, and Lockheed Martin among the anchors. The most sought-after specialties include natural language processing, computer vision, and MLOps platform engineering. Find a role that fits below and apply directly.
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Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential.
Job Title: ML Platform Engineer
Location: 100% Remote (U.S.)
Position Type: Full-time, Direct W2
Salary Range: $100,000–$160,000 Annually
Experience Required: 10+ years
Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position.
Job Summary:
We are seeking a ML Platform Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving.
Key Responsibilities
- Design and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendation systems.
- Optimize inference performance using continuous batching, paged attention, speculative decoding, and request multiplexing.
- Implement multi-tenant routing, rate limiting, and quality-of-service policies across model endpoints.
- Build autoscaling and capacity management systems that balance latency, throughput, and cost.
- Tune GPU utilization, memory management, and KV cache strategies for LLM serving workloads.
- Integrate model serving with API gateways, identity systems, and observability platforms.
- Implement caching, prompt deduplication, and response reuse strategies where appropriate.
- Drive end-to-end observability including latency histograms, queue dynamics, GPU utilization, and error tracking.
- Develop deployment workflows including canary releases, shadow testing, and automated rollback.
- Operate incident response for high-availability AI services and drive durable reliability improvements.
- Collaborate with ML and product teams to support new model releases and capability rollouts.
- Implement security controls including request signing, content filtering, and abuse detection at the serving layer.
- Document operational procedures, performance characteristics, and tuning guidance for internal teams.
- Stay current with AI serving research and translate advances into production capabilities.
- Bachelor’s or Master’s degree in Computer Science or a related field.
- 10 or more years of experience in distributed systems, infrastructure, or ML platform engineering.
- Strong proficiency in Python and a systems language such as Go, Rust, or C++.
- Deep experience operating high-throughput, low-latency services in production.
- Hands-on experience with LLM or large model inference frameworks such as vcLLM or TensorRT-LLM.
- Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.
- Familiarity with Kubernetes, autoscaling, and modern cloud platforms.
- Experience with observability stacks including metrics, tracing, and structured logging.
- Solid grounding in performance engineering and capacity planning.
- Strong communication and incident response skills.
- Open-source contributions to model serving infrastructure.
- Experience with multi-region or globally distributed AI serving.
- Familiarity with model quantization, distillation, and compression techniques.
- Exposure to FinOps for AI workloads and cost-efficient serving design.
- Experience supporting external-facing AI APIs at scale.
How to Apply
Would you like to know more about this opportunity? For immediate consideration, please send your resume to venkat.r@bvteck.com or contact us at (908) 505-3899. Learn more about Bright Vision Technologies at www.bvteck.com.
Bright Vision Technologies is an Equal Opportunity Employer.
Equal Employment Opportunity (EEO) Statement
Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall.
BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment.
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See All 37 ML Engineer Jobs in Pennsylvania
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Where Pennsylvania roles are concentrated, by current openings.
ML Engineer Job Market in Pennsylvania
A snapshot from current Pennsylvania openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Technology & Software
- Manufacturing
- Education
- Science & Research
What Pennsylvania Employers Look For
The qualifications that appear most often in ML engineer jobs across Pennsylvania.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
- Experience designing, training, and deploying production machine learning models at scale
- Familiarity with cloud platforms including AWS, Google Cloud, or Microsoft Azure for ML workloads
- Strong understanding of data pipelines, feature engineering, and model evaluation methodologies
- Ability to collaborate with cross-functional teams including data engineers, product managers, and software developers
ML Engineer Jobs in Pennsylvania: Frequently Asked Questions
How do you become a ml engineer in Pennsylvania?
Becoming an ml engineer in Pennsylvania typically starts with a bachelor's degree in computer science, mathematics, or a closely related field, though many roles prefer or require a master's degree. Pennsylvania has no state-issued license for ml engineers, so hiring is credential-driven: a strong portfolio of deployed models, demonstrated experience with industry-standard frameworks, and practical cloud certifications carry the most weight with Pennsylvania employers across industries like healthcare, finance, and defense.
Which companies hire ml engineers in Pennsylvania?
Employers hiring ml engineers in Pennsylvania right now include Penn State University, Carnegie Mellon University, and Motional, based on current listings on Migrate Mate as of September 2026. Pennsylvania's concentration of major health systems, financial services firms, and defense contractors means ml engineering roles here frequently touch regulated data environments and mission-critical applications.
Which Pennsylvania cities have the most ml engineer jobs?
Pittsburgh, University Park, and Horsham are the Pennsylvania cities with the most ml engineer openings. Philadelphia drives the largest share through its dense cluster of health systems, insurance companies, and fintech firms, while Pittsburgh's market is shaped by Carnegie Mellon University's robotics and AI programs and the anchor employers they have attracted to the region over decades.
Are there remote ml engineer jobs in Pennsylvania?
Yes, and more than most fields. About 43% of ml engineer openings tied to Pennsylvania are remote or hybrid as of September 2026, reflecting how naturally the work fits distributed settings. Model development, experimentation, and pipeline maintenance are the tasks most commonly performed fully remote, while roles requiring access to sensitive on-premises data, such as those at defense contractors or certain health systems, tend to require on-site presence.
How can I get hired as a ml engineer in Pennsylvania with little or no experience?
The most realistic entry path is a master's program or research assistantship at a Pennsylvania institution such as Carnegie Mellon, Penn, or Drexel, which regularly pipeline graduates into local employers. Candidates without a graduate degree can transition from data analyst or software engineering roles, building a portfolio of end-to-end projects on public datasets. Large Pennsylvania health systems and financial firms often post associate data scientist or junior ML roles that explicitly accept new graduates, making those a practical first target.
Where can I find and apply to ml engineer jobs in Pennsylvania?
You can find and apply to ml engineer jobs in Pennsylvania on Migrate Mate, which lists current openings across the state. Search the listings for roles that match your experience and specialty, then apply directly to the ones that fit.
See All 37 ML Engineer Jobs in Pennsylvania
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