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Google Machine Learning Engineer Jobs in Florida

Machine Learning & Operations Engineer

Miami, FL · Remote

$66.50K - $89.90K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

AI/Machine Learning Engineer Senior

Orlando, FL · On-site +1

$114.30K - $150.70K/yr

... machine learning and feature engineering techniques
 • Deploying AI capabilities and tracking projects through to completion
 • Implementing best technical practices from the fields of ...

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Google Machine Learning Engineer information

See Florida salary details

$23.5K

$96.2K

$144.6K

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

As of Jun 1, 2026, the average yearly pay for google machine learning engineer in Florida is $96,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,800.00 and $115,800.00 per year, depending on experience, location, and employer.

What is a Google Machine Learning Engineer job?

A Google Machine Learning Engineer designs, builds, and optimizes machine learning models to improve Google's products and services. They work with large datasets, implement algorithms, and deploy scalable AI systems. Collaboration with data scientists, software engineers, and product teams is essential to integrate models into real-world applications. Strong knowledge of Python, TensorFlow, and cloud computing is often required. This role focuses on both research and practical implementation to enhance automation and decision-making across Google products.

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

To thrive as a Google Machine Learning Engineer, you need strong expertise in mathematics, statistics, programming (especially Python or C++), and a solid background in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), cloud platforms (like Google Cloud), and advanced certifications can be highly beneficial. Excellent problem-solving, teamwork, and communication skills help you collaborate across teams and explain complex models to stakeholders. These skills are essential to driving innovation, building scalable solutions, and ensuring impactful results in a fast-paced, research-driven environment.

What types of projects and collaborations can Google Machine Learning Engineers expect to be involved in?

Google Machine Learning Engineers often contribute to diverse projects, such as developing next-generation search algorithms, optimizing user experiences across products, or creating scalable machine learning systems for internal and external clients. The role frequently involves collaborating with data scientists, product managers, software engineers, and researchers to define project goals and deliver impactful solutions. You can expect to participate in code reviews, prototype new models, and provide expert input during technical discussions. This collaborative, interdisciplinary approach ensures innovative outcomes and offers ongoing opportunities for professional growth and skill development.
What are the most commonly searched types of Google Machine Learning Engineer jobs in Florida? The most popular types of Google Machine Learning Engineer jobs in Florida are:
What cities in Florida are hiring for Google Machine Learning Engineer jobs? Cities in Florida with the most Google Machine Learning Engineer job openings:
Machine Learning & Operations Engineer

Machine Learning & Operations Engineer

OptiTrack

Miami, FL • Remote

$66.50K - $89.90K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 days ago


Job description

OptiTrack is a global leader in motion capture technology, delivering precision tracking solutions for animation, robotics, virtual production, biomechanics, and industrial applications.

About the Role

OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning. This role sits at the intersection of machine learning engineering and infrastructure, focusing on automation of data validation pipelines, orchestration of large-scale experiments, and deployment of high-performance algorithms.

This is a fully remote position, working cross-functionally with research and engineering teams.

What You'll Do

  • Design and maintain automated ML training pipelines.
  • Build infrastructure for large-scale distributed experimentation.
  • Develop CI/CD workflows tailored for machine learning systems.
  • Orchestrate data ingestion, preprocessing, validation, and model versioning.
  • Implement experiment tracking, hyperparameter tuning automation, and reproducibility systems.
  • Optimize GPU/compute utilization across cloud and on-prem environments.
  • Deploy, monitor, and maintain production ML models
  • Establish and enforce MLOps best practices including model registry, artifact management, and observability.
  • Improve system reliability, performance, and security.
  • Collaborate closely with ML researchers make new algorithms product ready.
  • More typical DevOps responsibilities for software development as required.

Requirements

Required Qualifications

  • 3+ years of experience in MLOps, ML infrastructure, Machine Learning, or related roles or relevant degree experience.
  • Experience with Python and ML frameworks (PyTorch, TensorFlow, or similar)
  • Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.)
  • Hands-on experience with containerization (Docker) and orchestration
  • Experience managing GPU workloads and distributed training systems
  • Experience with cloud platforms (AWS, GCP, or Azure)
  • Strong understanding of automation, infrastructure reliability, and data pipelines
  • Ability to work with both European and US developers.

Preferred Qualifications

  • Experience with motion capture or computer vision systems
  • Familiarity with experiment tracking tools (MLflow, Weights & Biases, etc.)
  • Background in distributed systems or high-performance computing
  • Experience with workflow orchestration tools (Airflow, Argo, Prefect, Kubeflow)
  • Infrastructure as Code experience (Terraform, Pulumi, CloudFormation)
  • Experience with model optimization, inference acceleration, or edge deployment
  • Experience building tracking algorithms for device localization using techniques like SLAM
  • Strong problem-solving skills and attention to reproducibility
  • Comfortable working in a remote, collaborative environment, with international team members
  • Clear communicator who can bridge research and production engineering
  • Experience with image rendering pipelines in CryEngine.
  • Passion for building scalable AI infrastructure

Why Join OptiTrack?

  • Work on cutting-edge motion tracking systems
  • Contribute to technology used across robotics, animation, virtual reality, biomechanics, and virtual production
  • Remote-first flexibility
  • Opportunity to shape the next-generation of motion capture technology

Benefits

All benefits start on first day of employment!

  • 75% employer-paid medical for employee. Family coverage also included. 
  • 100% employer paid dental, and vision for employee and dependents
  • 100% employer paid long-term, short-term disability, and life insurance policy
  • 401k Match, if you're contributing 5% we match 4%. 100% vested immediately.
  • 10 paid holidays
  • Starting at 15 days paid PTO (inclusive of sick and vacation time) annually
  • Employee Assistance Program (EAP)
  • Flexible Spending Account (FSA)

EEOC Statement:

OptiTrack is an equal opportunity employer, we believe in fostering a culture of equality, diversity, and inclusivity. Our commitment to this goal is clearly expressed in our zero-tolerance policy for discrimination and harassment of any kind, including on the basis of race, color, sex, age, religion, sexual orientation, national origin, disability, genetic information, pregnancy, protected veteran status or any other characteristic protected by applicable federal, state, or local laws. Our hiring practices ensure that decisions are based solely on qualifications, merit, and current business needs, while extending to all aspects of our operations - from recruitment and promotion to layoff and recall, to leave of absence, compensation, benefits, and training.  We are committed to remaining a drug free workplace