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Machine Learning Engineer Associate Jobs in Saint Augustine, FL

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

NGA AI Engineer Manager

Jacksonville, FL · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Currently, we are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Scientists, and Machine Learning engineers. Who Should Apply:

Specialized Analytics Senior Analyst

Jacksonville, FL · On-site

$79K - $100K/yr

Master's Degree or PhD preferred. 3+ years in data science, machine learning, or advanced analytics. Strong Technical Skills: Proficiency in programming languages such as Python, R, or SQL for data ...

Currently, we are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Scientists, and Machine Learning engineers. Who Should Apply:

Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization. * Communicate complex analytical ...

Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization. * Communicate complex analytical ...

Showing results 21-40

Machine Learning Engineer Associate information

See Saint Augustine, FL salary details

$36.2K

$72.1K

$115.1K

How much do machine learning engineer associate jobs pay per year?

As of Sep 15, 2026, the average yearly pay for machine learning engineer associate in Saint Augustine, FL is $72,081.00, according to ZipRecruiter salary data. Most workers in this role earn between $57,100.00 and $82,900.00 per year, depending on experience, location, and employer.

What is a machine learning engineer associate?

Machine Learning Engineer Associates are entry-level professionals who help design, build, and maintain machine learning models and systems. They typically work under the guidance of senior engineers, assisting in data preprocessing, model training, and testing. Their responsibilities may include implementing algorithms, evaluating model performance, and deploying solutions to production environments. This role requires a strong foundation in programming, statistics, and machine learning principles, often acquired through education or internships.

What are some common challenges faced by machine learning engineer associates when deploying models to production?

Machine Learning Engineer Associates often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and addressing issues with model drift after deployment. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, balancing model performance with resource constraints and maintaining clear documentation for reproducibility are important aspects of the role. Gaining familiarity with deployment tools and best practices can help overcome these hurdles.

What are the key skills and qualifications needed to thrive as a machine learning engineer associate, and why are they important?

To thrive as a Machine Learning Engineer Associate, you need a solid understanding of programming (especially Python), mathematics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with version control systems such as Git are essential. Strong problem-solving abilities, communication skills, and a collaborative mindset help you work effectively within technical teams. These competencies ensure you can develop, implement, and improve machine learning models that deliver actionable insights and drive business value.

What are the most commonly searched types of Machine Learning Engineer jobs in Saint Augustine, FL?

The most popular types of Machine Learning Engineer jobs in Saint Augustine, FL are:

What are popular job titles related to Machine Learning Engineer Associate jobs in Saint Augustine, FL?

For Machine Learning Engineer Associate jobs in Saint Augustine, FL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Associate jobs in Saint Augustine, FL look for?

The top searched job categories for Machine Learning Engineer Associate jobs in Saint Augustine, FL are:

What cities near Saint Augustine, FL are hiring for Machine Learning Engineer Associate jobs?

Cities near Saint Augustine, FL with the most Machine Learning Engineer Associate job openings:

Infographic showing various Machine Learning Engineer Associate job openings in Saint Augustine, FL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $72,081 per year, or $34.7 per hour.

Information Technology_USA - USA_Developer

Jacksonville, FL • On-site

Real Soft, Inc.
IT Services • 501 - 1,000 employees

Contractor

Re-posted 14 days ago


Job description

Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES B/T UNDERSCORES
: /hr- /hr MAX
PTN_US_GBAMSREQID_CandidateBeelineID
i.e. PTN_US_9999999_SKIPJOHNSON0413
MSP Owner: Shilpa Bajpai
Location: Basking Ridge, NJ- 100% onsite
Duration: 6 months
skill id: 10772179
Agentic AI, Python, LangChain, Vector databases, RAG pipelines, API integration
Role Descriptions:
Design| develop| and implement machine learning and AI models for business applications.
Build and optimize deep learning| NLP| or computer vision models depending on project requirements.
Deploy models into production using APIs| microservices| or cloud platforms.
Work with large datasets to clean| preprocess| and engineer features.
Monitor and maintain model performance| retraining when necessary.
Collaborate with cross-functional teams including product managers and data engineers.
Research and apply the latest developments in AI and machine learning.
Ensure scalability| security| and reliability of AI solutions.
Required Skills-
Technical Skills-Strong programming skills in Python (preferred) or Java C Experience with machine learning frameworks such as Tensor Flow Torch Scikit-learn
Knowledge of deep learning| NLP| computer vision| or generative AI
Role Descriptions:
Key Responsibilities:
• AI Development: Design and implement Generative AI applications using frameworks like LangChain, LlamaIndex, and LangGraph.
• Agentic Solutions: Build autonomous and semi-autonomous AI agents using AutoGen or CrewAI to solve complex business logic.
• Backend & APIs: Develop and maintain scalable REST APIs using FastAPI or Flask to serve AI models and services.
• Data Architecture: Manage and optimize data retrieval using Elasticsearch, NoSQL databases, and Graph databases like Neo4j.
• LLMOps & MLOps: Establish robust pipelines for model monitoring, evaluation, and deployment to ensure high performance and reliability.
• Full-Stack Integration: Collaborate with front-end teams to integrate AI features into React/Node.js environments.
Required Technical Skills:
• Languages: Expert-level Python (strong hands-on coding) and advanced SQL.
• Frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI.
• Databases: ElasticSearch, NoSQL, and Neo4j.
• AI/ML: Solid foundation in Machine Learning, Deep Learning, and LLM fine-tuning/prompt engineering.
• Backend: Proven experience with FastAPI or Flask for production APIs.
• Web: Familiarity with React and Node.js for full-stack AI integration.
Qualifications:
• Minimum 2+ years of experience as an AI Engineer or in a similar specialized Machine Learning role.
• Proven track record of deploying LLM-based applications to production.
• Strong understanding of vector embeddings, semantic search, and RAG architectures.
• Experience with Cloud environments (AWS/GCP/Azure) and CI/CD for ML (MLOps)., Project Code :