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Entry Level Machine Learning Engineer Jobs in Stratford, NJ

Comcast

Machine Learning Engineer 3- 7882

Philadelphia, PA · On-site +1

$56.25 - $74.50/hr

... programming and decomposition techniques; use machine learning techniques including tree-based models, linear and logistic regression, and time series models; use scikitlearn to create models ...

Varsity Tutors

Machine Learning Tutor

Chester, PA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

In this role, the Senior Machine Learning Engineer will bridge Data Science and Engineering to develop AI-based features and ensure the deployment of secure, reliable, and scalable machine learning ...

RELX Group plc

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

RELX

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global organization? Are you looking to drive cutting edge products that have a true societal impact? About ...

QTech US Inc

GenAI Engineer

Philadelphia, PA · On-site

Google Cloud Professional Machine Learning Engineer Certification. Google Cloud Professional Cloud Architect Certification. Experience with Llama Index. Experience with Hugging Face. Experience with ...

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All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Stratford, NJ

Entry Level Machine Learning Engineer information

See Stratford, NJ salary details

$29.5K

$68.2K

$115.9K

How much do entry level machine learning engineer jobs pay per year?

As of Jul 26, 2026, the average yearly pay for entry level machine learning engineer in Stratford, NJ is $68,156.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,600.00 and $77,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What cities near Stratford, NJ are hiring for Entry Level Machine Learning Engineer jobs? Cities near Stratford, NJ with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Stratford, NJ as of July 2026, with employment types broken down into 1% Locum Tenens, 92% Full Time, 4% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $68,156 per year, or $32.8 per hour.

Machine Learning Engineer (Inference Optimization)

DEEPREC.AI

Philadelphia, PA • On-site

$250K - $450K/yr

Full-time

Posted 22 days ago

Job description

Machine Learning Engineer - Inference Optimization
Overview
We are looking for a Machine Learning Engineer focused on low-latency inference optimization to help build, tune, and productionize high-performance model serving systems. This role sits at the intersection of machine learning, systems engineering, and GPU performance. You will work on inference workloads where latency, throughput, reliability, and hardware efficiency all matter, and where a deep understanding of modern inference runtimes can meaningfully improve production outcomes.
You will work closely with researchers and engineers to understand model structure, identify inference bottlenecks, and turn research ideas into efficient production systems. The work may involve other types of models, but focuses on transformer-style architectures and structured inference workloads. You will evaluate and tune frameworks and related serving or compilation systems, while also reasoning about GPU execution, memory layout, batching strategies, precision tradeoffs, and end-to-end latency.
What you'll do:
  • Design, build, and optimize low-latency inference systems for production machine learning workloads.
  • Profile model inference pipelines across model execution, runtime configuration, batching, memory movement, serialization, networking, and I/O.
  • Evaluate, integrate, and tune inference runtime systems.
  • Improve latency, throughput, and GPU utilization for production inference workloads.
  • Build and support benchmarking and profiling tools to compare model variants, hardware targets, runtime configurations, and deployment strategies.
  • Debug performance issues involving GPU memory, compute saturation, kernel behavior, CPU/GPU coordination, data movement, and serving-layer overhead.
  • Help shape model and system design choices so that research models are efficient to deploy under real latency constraints.
  • Where necessary, collaborate with lower-level systems or GPU specialists on custom operators, kernel-level optimization, or hardware-specific performance work.
What we're looking for:
  • Experience deploying, optimizing, or operating machine learning inference workloads in production or production-like environments.
  • Programming experience in Python, Java, C# etc. and at least one systems language such as C, C , Rust, or Go.
  • Solid understanding of modern ML frameworks such as PyTorch, including model execution, export, tracing, compilation, and performance profiling.
  • Ability to reason about latency, throughput, batching, memory use, GPU utilization, and reliability under real workloads.
  • Strong practical judgment around tradeoffs between model quality, latency, throughput, implementation complexity, and maintainability.
Preferred qualifications:
  • Experience optimizing inference for latency-sensitive or high-throughput applications.
  • Experience with model optimization techniques such as quantization, pruning, distillation, operator fusion, graph lowering, custom operators, or model compilation.
  • Exposure to CUDA, Triton language, ROCm, PTX, CuTe, CUTLASS, FlashInfer, or similar low-level GPU programming tools.
  • Experience running inference workloads on Kubernetes or GPU clusters, including scheduling, autoscaling, observability, and resource management.
  • Background in mathematics, physics, computer science, engineering, statistics, or another technical field.
  • Demonstrated ability to improve real-world inference performance beyond a baseline framework implementation.

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