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Deep Learning Engineer Jobs in Florida (NOW HIRING)

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and ...

Citadel

Deep Learning ML Researcher

Miami, FL

Models incorporate advanced techniques: deep learning, sequence / time-series models ... Our teams of engineers, traders and researchers harness leading-edge quantitative research and the ...

Citadel

Machine Learning Engineer

Miami, FL

You will combine the best available open-source tools with deep internal expertise in modelling and ... learning and software development. * Strong engineering skills, including Python, CUDA, C+

ClifyX

Sr. Machine Learning Engineer

Bradenton, FL · Remote

$111K - $146K/yr

This role possesses an in-depth subject matter expertise of design, Machine Learning, AI/Deep Learning, software development, coding, testing and application programming and assists in aligning ...

ENSCO

Machine Learning Engineer

Melbourne, FL

$72K - $131K/yr

Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL · On-site

$73K - $131K/yr

Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks ...

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All JobsDeep Learning Engineer JobsDeep Learning Engineer Jobs in Florida

Deep Learning Engineer information

See Florida salary details

$28.4K

$86.6K

$143.1K

How much do deep learning engineer jobs pay per year?

As of Jun 17, 2026, the average yearly pay for deep learning engineer in Florida is $86,585.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,000.00 and $113,200.00 per year, depending on experience, location, and employer.

What is a Deep Learning Engineer job?

A Deep Learning Engineer is a specialized software engineer who designs, develops, and optimizes deep learning models. They work with neural networks, large datasets, and frameworks like TensorFlow or PyTorch to build AI systems for tasks like image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, performance tuning, and deploying models into production. Strong programming skills in Python, knowledge of machine learning algorithms, and experience with GPU acceleration are essential for this role.

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

To thrive as a Deep Learning Engineer, you need a strong background in mathematics, machine learning theory, and programming (especially Python), often supported by a relevant degree in computer science, engineering, or related fields. Proficiency with frameworks such as TensorFlow, PyTorch, Keras, as well as experience with GPUs and cloud platforms, is highly valued, and certifications in AI or deep learning can further enhance your profile. Effective problem-solving, strong collaboration skills, and clear communication are important soft skills for excelling in interdisciplinary teams. These abilities ensure that you can develop robust deep learning models, adapt to evolving technologies, and contribute value in both technical and collaborative settings.

What are the typical daily tasks and responsibilities of a Deep Learning Engineer?

Deep Learning Engineers typically spend their days designing, developing, and optimizing neural network models for tasks like image recognition, natural language processing, or recommendation systems. They preprocess and analyze large datasets, experiment with model architectures, and tune hyperparameters to achieve the best performance. Collaboration is often required with data scientists, product managers, and software engineers to integrate models into real-world applications and scale solutions for production. Additionally, many deep learning engineers review current research, stay updated on advancements in AI, and continuously improve their skills. This role offers a dynamic work environment where learning and innovation are highly encouraged.

What are the most commonly searched types of Deep Learning Engineer jobs in Florida? The most popular types of Deep Learning Engineer jobs in Florida are:
What are popular job titles related to Deep Learning Engineer jobs in Florida? For Deep Learning Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Deep Learning Engineer jobs in Florida look for? The top searched job categories for Deep Learning Engineer jobs in Florida are:
What cities in Florida are hiring for Deep Learning Engineer jobs? Cities in Florida with the most Deep Learning Engineer job openings:
Deep Learning Engineer jobs near you
Infographic showing various Deep Learning Engineer job openings in Florida as of June 2026, with employment types broken down into 10% Internship, 71% Full Time, and 19% Contract. Highlights an 96% In-person, and 4% Hybrid job distribution, with an average salary of $86,585 per year, or $41.6 per hour.

Deep Learning Robot Manipulation Engineer

Persona AI

Pensacola, FL • On-site

Full-time

Posted 18 hours ago

Job description

We're looking for a Deep Learning Manipulation Engineer to help train Persona AI robots to do real work in real world environments. We're looking for exceptional people who dream big, thrive on challenges, and love seeing their efforts come to life. We are primarily interested in candidates who have developed and released products to the market, but can be flexible depending on aptitude and energy.
As one of the inaugural Deep Learning Manipulation Engineers at Persona, you will have an incredible opportunity to get in at the beginning to shape the design and development of Persona's deep learning and manipulation strategy and infrastructure. If you're passionate about cutting-edge technology and want to be part of a world-class team we'd love to hear from you.
Your Role:
  • Design and implement advanced deep learning models and training procedures to achieve dexterous manipulation for humanoid robots with high DOF and multi-fingered hands.
  • Train models, using curriculum learning strategies, to progress from simple object interactions to precise grasping, long-horizon tasks, tool-use, and in-hand object manipulation.
  • Incorporate tactile sensing and proprioception into end-to-end learning pipelines, enabling robust closed-loop policies.
  • Work with the teleoperation and data team to design data collection and versioning strategies.
  • Leverage existing state-of-the-art manipulation models and contribute to the development of new architectures for emerging complex tasks.
  • Deploy trained manipulation models to robotic hardware, ensuring real-time performance, safety, and integration with control systems and sensors.
  • Collaboratively develop and optimize the manipulation ML pipeline.
  • Keep up to date with the state of the art in research and development.
  • Develop and execute evaluation pipelines to rigorously test learned manipulation models, including real-world trials and simulation, measuring performance, robustness, and generalization across tasks and environments.
  • Collaborate in attracting, nurturing and growing the machine learning and autonomy teams.

We're Looking For:
  • Courage and grit to tackle some of the hardest problems in robot manipulation.
  • Enthusiasm for working collaboratively in fast paced ambiguous environments.
  • Masters or PhD in Robotics, Computer Science, or a related field.
  • 3+ years of experience in applying deep learning to robotic manipulation.
  • Strong understanding and proficiency with state of the art algorithms and best-practices in behavior cloning, vision-language-action models, diffusion policies, foundation models, etc.
  • Experience with cloud computing and large-scale datasets.
  • Understanding of the challenges of deploying neural network models in the real world.
  • Capable of writing high quality software.
  • Strong first principles thinker.

Preferred or Bonus Qualifications:
  • Experience with other aspects of ML applied to robotics, including computer vision algorithms, sensors, point clouds, segmentation and object detection.
  • Published papers at top ML/Robotics conferences (ICML, ICRA, CoRL, RSS, NeurIPS).
  • Have deployed robots, collected large amounts of data, and trained large neural networks that work in production environments.

Apply