ZipRecruiter

Log In

1

Afternoon Full Stack Machine Learning Engineer Jobs

Aquabyte

Machine Learning Engineer

Pittsburgh, PA · On-site +1

$110K - $165K/yr

... stack. Above all, Aquabyte is a customer-driven company. Our product development is dictated by the ... The role As a Machine Learning Engineer you will be responsible for developing Machine Learning ...

Aquabyte

Machine Learning Engineer

San Francisco, CA · On-site

$130K - $170K/yr

... stack. Above all, Aquabyte is a customer-driven company. Our product development is dictated by the ... The role As a Machine Learning Engineer you will be responsible for developing Machine Learning ...

Aquabyte

Machine Learning Engineer

Pittsburgh, PA · Remote

... stack. Above all, Aquabyte is a customer-driven company. Our product development is dictated by the ... The role As a Machine Learning Engineer you will be responsible for developing Machine Learning ...

NT Concepts

Machine Learning Engineer

Herndon, VA · On-site

... stacks, and constantly challenge each other to grow and improve. If cutting edge data science ... As a Machine Learning Engineer, you'll be part of the Agile team delivering machine learning ...

Inovalon

Senior Machine Learning Engineer

Atlanta, GA · On-site

$117.80K - $155.30K/yr

... full model development lifecycle on a modern, cloud-native AWS stack. Responsibilities : • Design, train, and deploy machine learning models spanning classical ML (classification, regression ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Machine Learning Engineer LOCATIONTysons, VA 22182 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Chantilly, VA

Machine Learning Engineer LOCATIONChantilly, VA 20151 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Cymertek

Machine Learning Engineer

Aurora, CO

Machine Learning Engineer LOCATIONAurora, CO 80014 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative Machine ...

Virtusa

Machine Learning Engineer

Minneapolis, MN · On-site

Nice to have:- - Experience with feature stores, model registries, and model monitoring stacks ... Role Summary:- Builds, trains and tunes machine learning models. Translates data science ...

Cymertek

Machine Learning Engineer

San Antonio, TX

Machine Learning Engineer LOCATIONSan Antonio, TX 78208 CLEARANCETS/SCI Full Poly (Please note this position requires full U.S. Citizenship) KEY SUMMARYWe are seeking a talented and innovative ...

Nace AI

Machine Learning Engineer

Palo Alto, CA · On-site

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine ... Familiarity with data processing stacks such as Spark and Airflow. * Experience with multi-node GPU ...

Pelica Health

Machine Learning Engineer

... full machine learning lifecycle: data preparation, train/test splitting, evaluation, deployment, retraining, and monitoring. • Solid backend engineering skills: writing production-quality code ...

next page

Showing results 1-20

People also search for

All JobsAfternoon Full Stack Machine Learning Engineer Jobs

Afternoon Full Stack Machine Learning Engineer information

See salary details

$44.5K

$134.8K

$190.5K

How much do afternoon full stack machine learning engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for afternoon full stack machine learning engineer in the United States is $134,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $158,000.00 per year, depending on experience, location, and employer.
More about Afternoon Full Stack Machine Learning Engineer jobs
What cities are hiring for Afternoon Full Stack Machine Learning Engineer jobs? Cities with the most Afternoon Full Stack Machine Learning Engineer job openings:
What are the most commonly searched types of Full Stack Machine Learning Engineer jobs? The most popular types of Full Stack Machine Learning Engineer jobs are:
What states have the most Afternoon Full Stack Machine Learning Engineer jobs? States with the most job openings for Afternoon Full Stack Machine Learning Engineer jobs include:
What job categories do people searching Afternoon Full Stack Machine Learning Engineer jobs look for? The top searched job categories for Afternoon Full Stack Machine Learning Engineer jobs are:
Afternoon Full Stack Machine Learning Engineer jobs near you
Infographic showing various Afternoon Full Stack Machine Learning Engineer job openings in the United States as of May 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $134,771 per year, or $64.8 per hour.
Machine Learning Software Engineer II

Machine Learning Software Engineer II

Cambium Learning Group

Dallas, TX • On-site, Remote

$89.90K - $123.10K/yr

Full-time

Posted 26 days ago

Cambium Learning Group rating

9.2

Company rating: 9.2 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

12th of 184 rated software companies

Job description

Cambium Learning® Group is an award-winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction. Using a research-based, personalized approach, Cambium Learning Group delivers SaaS resources and instructional products that engage students and support teachers in fun, positive, safe and scalable environments. These solutions are provided through Learning A-Z® (online differentiated instruction for elementary school reading, writing and science), ExploreLearning® (online interactive math and science simulations, a math fact fluency solution, and a K-2 science solution), Voyager Sopris Learning® (blended solutions that accelerate struggling learners to achieve in literacy and math and professional development for teachers), and VKidz Learning (online comprehensive homeschool education and programs for literacy and science). We believe that every student has unlimited potential, that teachers matter, and that data, instruction, and practice are the keys to success in the classroom and beyond.
Job Overview:
We are seeking a talented Machine Learning Engineer II to join our CAI machine learning and scoring development team. In this role, you will be the crucial bridge between applied research and production systems. Working alongside a cross-functional group of mathematicians, computer scientists, psychometricians, and statisticians, you will design and deploy custom machine learning solutions for our clients and internal platforms.
The ideal candidate is a full-stack ML practitioner who is equally comfortable discussing algorithmic design with researchers and architecting scalable, low-latency production systems. You will own the full software development lifecycle-transforming research prototypes into optimized, production-ready solutions using modern AWS infrastructure such as SageMaker, ECS, and Lambda, with an emphasis on high-throughput inference and PyTorch-to-ONNX model optimization.
Job Responsibilities:
  • Full-Lifecycle ML Development: Lead the transition of machine learning models from theoretical prototypes into scalable, high-performance production systems.
  • AWS Cloud Architecture & Deployment: Architect and deploy ML solutions utilizing AWS ECS (Elastic Container Service) for containerized workloads and AWS Lambda for serverless, event-driven inference pipelines.
  • Model & Inference Optimization: Optimize PyTorch models for production deployment by converting them to ONNX formats. Apply advanced inference optimization techniques (quantization, pruning, ONNX Runtime) and memory-efficient attention mechanisms like Flash Attention to minimize latency and maximize throughput.
  • Infrastructure & Engineering Best Practices: Champion infrastructure best practices for machine learning systems, establishing reliable CI/CD pipelines, and ensuring robust, secure, and reproducible deployments across the AWS ecosystem.
  • Algorithm Engineering: Design, develop, and evaluate algorithms that generate descriptive, diagnostic, predictive, and prescriptive insights from both structured and unstructured data.
  • Robust Software Engineering: Write clean, efficient, and well-tested code. Complete rigorous testing, debugging, and documentation to ensure seamless installation and long-term maintenance.
  • Cross-Functional Collaboration: Actively participate in research discussions, requirements gathering, and system design alongside domain experts to build tailored scoring and ML solutions.

Job Requirements:
  • Experience: 2-5 years of industry experience in Machine Learning Engineering, Software Engineering, or Data Science, with a proven track record of architecting and deploying models to production.
  • Cloud & MLOps Infrastructure: Deep, hands-on experience with the AWS ecosystem, specifically AWS ECS and Lambda. Solid understanding of containerization (Docker) and event-driven architectures.
  • Programming Proficiency: Strong proficiency in modern programming languages used in ML (e.g., Python, C++, Java) and familiarity with industry-standard coding practices.
  • ML Frameworks & Advanced Optimization: Hands-on experience with PyTorch and other machine learning libraries (e.g., Scikit-Learn, TensorFlow). Deep understanding of model optimization pipelines, including PyTorch to ONNX conversions, ONNX Runtime, and scaling attention mechanisms (e.g., Flash Attention).
  • Data Systems: Experience working with large-scale computing frameworks, data analysis systems, and relational/non-relational databases.

Nice to Have's:
  • AWS SageMaker: Experience utilizing AWS SageMaker for managed model training and hosting.
  • Advanced LLMOps & Fine-Tuning: Hands-on experience applying modern parameter-efficient fine-tuning methods (such as LoRA and qLoRA) to large language models.
  • AI Agents: Experience building, integrating, and deploying autonomous or semi-autonomous AI agents to automate complex workflows and connect ML models with external tools/APIs.
  • NLP Expertise: Proven experience and familiarity with deep learning technologies applied specifically to Natural Language Processing (NLP) and complex text-based modeling.
  • Cross-Disciplinary Collaboration: Experience collaborating with specialized researchers (e.g., psychometricians, statisticians) to operationalize complex mathematical concepts.
  • Infrastructure as Code: Experience implementing IaC using tools like Terraform or AWS CloudFormation.
  • Model Monitoring: Experience setting up comprehensive model monitoring systems to detect data drift, concept drift, and model degradation in production AWS environments.

To apply for this opportunity, simply click on the "Apply" button and submit a cover letter and resume.
An Equal Opportunity Employer
We are dedicated to fostering a culture that celebrates unique backgrounds, ideas, and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

Apply