ZipRecruiter

Log In

1

Temporary Machine Learning Software Engineer Jobs in Plymouth, MA

Spear AI

Embedded DevOps Engineer

Falmouth, MA · On-site

... the software team includes a diverse group of Data, Design, Full Stack, Infrastructure, and Machine Learning engineers. Successful candidates will work well with both teams and bridge the gap to ...

Spear AI

Embedded DevOps Engineer

Falmouth, MA · On-site

... the software team includes a diverse group of Data, Design, Full Stack, Infrastructure, and Machine Learning engineers. Successful candidates will work well with both teams and bridge the gap to ...

Nestlé S.A.

Senior Data Scientist

Bridgewater, MA · On-site

$130 - $160/hr

Hands‑on programming experience in Python and R, leveraging advanced cognitive and machine learning methods to solve business challenges. * Experience working with relational database and cloud ...

New

previous pagenext page

Showing results 21-40

All JobsMachine Learning Software Engineer JobsTemporary Machine Learning Software Engineer JobsTemporary Machine Learning Software Engineer Jobs in Plymouth, MA

Temporary Machine Learning Software Engineer information

See Plymouth, MA salary details

$26.1K

$114.1K

$205.7K

How much do temporary machine learning software engineer jobs pay per year?

As of Aug 9, 2026, the average yearly pay for temporary machine learning software engineer in Plymouth, MA is $114,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,700.00 and $130,600.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Machine Learning Software Engineer vs Data Scientist?

AspectTemporary Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master's in CS, ML, or related fields; coding skillsBachelor's or Master's in CS, Statistics, or related fields; analytical skills
Work EnvironmentSoftware development teams, project-based rolesData analysis teams, research-focused roles
Employer & Industry UsageTech companies, startups, consulting firmsFinance, healthcare, tech, research institutions
Search & Comparison IntentOften compared for technical roles involving ML implementationCompared for data analysis and modeling expertise

The main difference is that a Temporary Machine Learning Software Engineer focuses on developing and deploying ML models within software projects, while a Data Scientist emphasizes data analysis, statistical modeling, and deriving insights from data. Both roles require strong technical skills, but their focus areas and typical tasks differ.

What cities near Plymouth, MA are hiring for Temporary Machine Learning Software Engineer jobs? Cities near Plymouth, MA with the most Temporary Machine Learning Software Engineer job openings:
Temporary Machine Learning Software Engineer jobs near you

Generative AI Automation Engineer - Remote Job

EnthuZiastic

North Dartmouth, MA • On-site

Other

Re-posted 19 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply