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Remote Java Machine Learning Jobs in Florida (NOW HIRING)

OptiTrack

Machine Learning & Operations Engineer

Miami, FL · Remote

$66.50K - $89.90K/yr

This is a fully remote position, working cross-functionally with research and engineering teams ... Develop CI/CD workflows tailored for machine learning systems. * Orchestrate data ingestion ...

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What are the key skills and qualifications needed to thrive as a Remote Java Machine Learning Engineer, and why are they important?

To excel as a Remote Java Machine Learning Engineer, you need strong programming skills in Java, a solid understanding of machine learning algorithms, and typically a degree in computer science or a related field. Familiarity with machine learning frameworks (such as TensorFlow or Weka), version control systems like Git, and cloud computing platforms is highly valued. Excellent problem-solving, communication, and self-motivation are crucial soft skills for remote collaboration and project delivery. These competencies are vital for building effective ML solutions, working independently, and ensuring seamless integration within distributed teams.

How does a Remote Java Machine Learning Engineer typically collaborate with cross-functional teams given the distributed work environment?

As a Remote Java Machine Learning Engineer, you will regularly collaborate with data scientists, software engineers, and product managers through virtual meetings, shared project management tools, and code repositories. Clear communication and proactive documentation are essential to ensure alignment, especially when integrating machine learning models into Java-based applications. You may also participate in code reviews, sprint planning, and brainstorming sessions to refine features and troubleshoot issues. Building strong working relationships remotely often involves actively engaging in team channels and being responsive to feedback.

What are Remote Java Machine Learning jobs?

Remote Java Machine Learning jobs involve developing, deploying, and maintaining machine learning models and applications using the Java programming language, all while working from a remote location. Professionals in these roles typically build algorithms, process data, and integrate machine learning solutions into software systems. They collaborate with other developers and data scientists virtually, leveraging Java libraries such as Weka, Deeplearning4j, or MOA. These jobs are ideal for those who have strong Java skills and a background in machine learning, and who prefer the flexibility of working remotely.
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Remote Java Machine Learning jobs near you
Senior Software Engineer, Machine Learning

Senior Software Engineer, Machine Learning

RIT Solutions, Inc.

Tampa, FL • Remote

$70/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Senior Software Engineer, Machine Learning
Notes:
Senior Software Engineer, Machine Learning (638)
Experience: 4-8 yrs
Remote; The team is currently working across ET and PT time zones
Rate: $70/hr
7 Months; Nov 11, 2024 - Jun 20, 2025
Specific tool requirements & programs/software used? Python, Tensorflow, Scala
Interview process: Phone Screen, Technical
Technical Skills:
Must Have
Experience in machine learning techniques, pipelines and applications
Experience with writing robust, idiomatic and easy-to-understand backend code (Python, Java, Scala).
Experience writing scalable and performant data pipelines on distributed systems (e.g. Hadoop, Spark) - preference in candidates with experience in Airflow
Nice To Have
Experience with cloud platforms like GCP or AWS
Familiar with ML lifecycle: training, deploying, monitoring, debugging, and iterating on production machine learning systems.
Familiar with modern machine learning frameworks such as TensorFlow or Pytorch.
Requirements
Must-Haves

  • Solid engineering & coding skills and proficiency in at least one programming language of Python, Scala, or Java.
  • Experience with writing scalable and performant data pipelines on distributed systems
  • Familiar with machine learning techniques and applications

Nice-to-Haves
  • Hand-on experience in machine learning frameworks & technologies such as Tensorflow / TFX, Pytorch, Kubeflow.
  • Experience with the ML lifecycle: training, deployment, monitoring, debugging and iterating on production machine learning systems
  • Familiar with Google Cloud Platform and products such as Dataflow, Vertex AI

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