opportunities, with a focus on continuous learning and skills development to become a... ...maintaining production-grade ML and DL models, machine learning workflows, and pipelines... ...years of related work experience…
Engineering & IT · Philadelphia, PA
Machine Learning Engineer jobs in Philadelphia, PA
Machine learning engineers take models from notebook to production — building training pipelines, serving infrastructure, and monitoring so ML systems keep working after launch.
158
Open roles today
$47–$119/hr
Typical pay range
$159k
Median, full-time
6
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01
Open machine learning engineer roles
12 shown of 158 · sorted by freshness
The H&K Group, Inc. i s searching for a Project Engineer! The ideal candidate is a self-motivated, organized, competent, and professional individual who manages the planning, design and permitting of civil engineering pr…
company of the future. Job Summary The Sr Field Electrical Engineer provides technical, logistical, and administrative support to... ...Sessions Commuter and Flexible Spending Accounts Learn more about our benefits offer…
$35 - $38 per hour
Internal Our MedTech Field Service Engineer experiences a unique opportunity employ their technical experience by collaborating... ...expand into new opportunities while earning supplemental income and learning the medic…
$123.6k - $162.3k
facilities; it’s about well-designed strategies tailored for every and every location. We're looking for a high-energy, Plumbing Engineer to join our Building Mechanical team and help deliver innovative Plumbing design s…
$132.9k - $182.7k
grow, and succeed – today and into tomorrow. As an Electrical Engineer in our Advanced Manufacturing group, you’ll contribute to... ...Analytical and problem-solving skills Forward thinking, eager to learn best practices…
$132.9k - $182.7k
hire the "best" candidates. We're looking for a Senior Civil Engineer to join our Data Center group, and you'll have the chance to... ...due diligence and development teams ~ Demonstrated ability to learn quickly and bro…
Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role will primarily focus on building, validat…
$75k - $95k
Our client, a manufacturing company, is hiring a Field Service Engineer to install, maintain, and repair industrial machinery at customer sites throughout the greater Philadelphia region. This role combines hands-on mech…
of transactions, make intelligent decisions, and continuously learn from real-world financial data. This is your chance to shape how... ...(trading, risk, compliance, or banking) Knowledge of prompt engineering and in-co…
$65k - $79k
Job Details: Commercial Office Building Engineer - Plymouth Meeting, Pa $65-79k *EPA Universal Certification is required! Position Summary The Commercial Office Building Engineer is responsible for the daily operation, m…
$110k - $120k
Job Description — Field Service Engineer II (LINAC) | Direct Hire (W2) Position: Field Service Engineer II (FSE II) – Linear Accelerators... ...discussed during interview). Engineers typically support 2–3 machines on ave…
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What machine learning engineers earn in Philadelphia
Hourly first — that's how the offer arrives
| Experience | Hourly | Annual, full-time |
|---|---|---|
| Entry level | $47–$65 | $97k–$135k |
| Mid level | $65–$88 | $135k–$184k |
| Senior | $86–$119 | $178k–$248k |
Adjusted for the Philadelphia market from national ranges.
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What employers ask for
The skills these listings keep naming
Python and software engineeringPyTorch or TensorFlowML fundamentals and evaluationModel serving and APIsMLOps (tracking, registries, CI)Docker and KubernetesData pipelines and feature storesLLM fine-tuning and RAG (a plus)Monitoring and drift detection
04
Interview questions worth rehearsing
With the thing the interviewer is actually listening for
Walk me through taking a model from prototype to production.
Cover data pipelines, training reproducibility, serving, and monitoring. Emphasize that the model is a small part of the system — that framing is the job.
How do you monitor a model in production?
Discuss input drift, prediction distributions, delayed labels, and business metrics — plus what triggers retraining. Mention that silent degradation is the default failure mode.
How would you reduce inference latency or cost for a large model?
Options include distillation, quantization, batching, caching, and smaller models. Frame it as measuring first, then choosing the cheapest acceptable quality tradeoff.
Tell me about a time a model failed in production. What happened?
A real story about skew, drift, or a data bug — with detection and prevention — is far more convincing than claiming smooth deployments.
How do you evaluate a model beyond accuracy?
Talk about the metric matching the business cost of errors, slicing by segment, and offline-online gaps. Naming a case where accuracy misled is a strong touch.
When would you fine-tune an LLM versus use retrieval or prompting?
Start cheap: prompting, then RAG for knowledge, fine-tuning for behavior and format. Cost and maintenance burden should drive the answer.
How do you make training reproducible?
Version code, data, and config; track experiments; pin environments. This is engineering discipline applied to ML, which is exactly the role.
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Resume tips that move the needle
For machine learning engineers specifically — generic advice costs you here
01
Center bullets on production systems: models served, request volume, latency, and the business metric they moved.
02
Show software engineering credentials explicitly — testing, CI, code review — since MLE hiring filters hardest on engineering rigor.
03
Name the MLOps tooling you have run (MLflow, SageMaker, Kubeflow, vector databases) as these are common screens.
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Include LLM work with specifics — fine-tuning, RAG, evaluation — if you have it; vague 'GenAI experience' claims read poorly.
05
Distinguish your role on shared projects: built the serving layer, owned the pipeline, or trained the model.
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Where this role goes
Typical progression
01
ML Engineer
02
Senior ML Engineer
03
Staff ML Engineer
04
ML Platform Lead
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