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Junior Machine Learning Jobs in Florida (NOW HIRING)

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

... machine-learning and AI methods (e.g., neural networks, SVM). * Provide expert consultation on ... Mentor junior statisticians, faculty, trainees, and research staff. * Participate in abstract ...

... machine-learning and AI methods (e.g., neural networks, SVM). * Provide expert consultation on ... Mentor junior statisticians, faculty, trainees, and research staff. * Participate in abstract ...

Senior Data Engineer

Miami, FL · On-site

$101K - $137K/yr

... machine learning, and product initiatives • Ensure data quality, integrity, security, and ... junior data engineers through technical guidance and knowledge sharing • Contribute to ...

Design, develop, and deploy enterprise AI solutions spanning traditional machine learning ... Mentor junior AI engineers and elevate the broader organization's AI engineering capabilities

Design, develop, and deploy enterprise AI solutions spanning traditional machine learning ... Mentor junior AI engineers and elevate the broader organization's AI engineering capabilities

... machine learning algorithms and predictive modeling to solve complex business problems - Creating ... junior team members and fostering a collaborative team environment What You Must Have - At least a ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

Full Stack/Java Developer(REMOTE)

Orlando, FL · On-site

$49 - $63.25/hr

SynergisticIT is looking for motivated candidates interested in entry-level and junior roles in ... Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or ...

... and machine learning techniques to large-scale claims, clinical, and member data to surface ... junior staff while securing project success and maintaining exemplary standards. This role offers ...

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Showing results 1-20

Junior Machine Learning information

What is the difference between Junior Machine Learning vs Data Scientist?

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise with tools like TensorFlow or PyTorch, and may require multiple years of experience and relevant certifications.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within top tech companies. Compensation often includes base salary, bonuses, and stock options. Achieving this level typically requires years of specialized experience and a strong track record of impactful projects.

Can I get an AI job with no experience?

Entry-level machine learning roles, such as Junior Machine Learning positions, often require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is beneficial, candidates can improve their chances by completing relevant online courses, building projects, and gaining familiarity with tools like Python and TensorFlow.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and machine learning engineers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
What are the most commonly searched types of Machine Learning jobs in Florida? The most popular types of Machine Learning jobs in Florida are:
What cities in Florida are hiring for Junior Machine Learning jobs? Cities in Florida with the most Junior Machine Learning job openings:
Infographic showing various Junior Machine Learning job openings in Florida as of July 2026, with employment types broken down into 88% Full Time, 8% Part Time, 2% Temporary, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution.
Senior AI Engineer - SFL Scientific

Senior AI Engineer - SFL Scientific

Deloitte

Tampa, FL

$98K - $135K/yr

Other

Re-posted 15 hours ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 90 frontline employees who took The Breakroom Quiz

59th of 148 rated financial services


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Master's degree in Computer Science, Engineering, Physics, etc. or related STEM field
  • AWS/Azure Certifications (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect)
  • 2+ years of experience with GPU computing (CUDA, OpenCL) and HPC system software stack

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $128,000 to $252,500.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
Are you eager to shape the future of emerging technologies? Imagine joining an acclaimed team where career paths span from account executives and data scientists to AI strategists, machine learning specialists, and data engineers. SFL Scientific, a Deloitte Business, is looking to add a Senior AI Engineer to their vibrant environment. SFL Scientific is part of our broader Strategy Offering within the Strategy & Transactions practice, whose specialized team brings together key capabilities to design integrated solutions that drive transformational change for our clients. Take the next step in your technical journey-develop your leadership, consulting acumen, and reputation as a trailblazer within the AI engineering field by joining our team!

Recruiting for this role ends on 8/31/2026.

Work You'll Do
As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and deployment services for our novel machine learning applications. Key to this role is the ability to demonstrate both traditional data engineering expertise, leveraging cloud/enterprise/open-source solutions, and constructing IT infrastructure for organizations across a wide variety of industries.

In our consultative approach, we are platform agnostic and committed to providing the best technical solutions for each client and solution. Our engineering team leverages emerging technologies and best practices across data security, documentation, cloud services and engineering architecture to create solutions and products that address complex issues and business problems faced by global organizations. Some of our novel use cases include cancer detection, drug discovery, optimizing population health and clinical trials, autonomous systems and edge AI, and renewable energy. Key responsibilities:

  • Work with clients to design, develop, and deploy new architectures to support machine learning & automation applications
  • Leverage advanced technical skills in modern data architecture, data science engineering, data transformation, and management of structured and unstructured data sources using cloud computing or on-prem technologies
  • Design and lead development on scalable, high-performance data architecture solutions that supports both the client business as well as AI/GenAI use cases
  • Support and enhance data architecture, and data pipelines, and define database schemas (Graph, SQL, NoSQL) to develop algorithm scalability and deployment based on agile business priorities and initiatives
  • Participate in architectural and deployment discussions to ensure solutions are designed for successful scale, security, and high availability in the cloud or on prem
  • Adopt best engineering practices in automation, HPC and AI/GenAI infrastructure and design patterns
  • Define and lead technology proof of concepts to ensure feasibility of new data and cloud technology solutions
  • Display strong thought leadership and execution in pursuit of modern data architecture principles and technology modernization
  • Mentor, motivate, and coach junior members on technical best practices and inspire professional development

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

The Team

Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.
Qualifications

Required:

  • Bachelor's degree in a STEM field (Computer Science, Engineering, Physics, etc.) or equivalent experience
  • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment
  • 4+ years of experience in designing cloud solutions and supporting production projects, including hands-on experience with AWS services (or Azure, GCP equivalents)
  • 4+ years of programming experience with Linux Shell/CLI, Python, SQL, PowerShell, etc.
  • 2+ years of experience managing teams in technical delivery and delivering complex and critical projects
  • 2+ years of experience in DevOps and leveraging CI/CD services: Puppet, Ansible, Chef, Airflow, Terraform, Jenkins
  • 2+ years of experience with database development and ETL/ELT pipelines (relational, NoSQL, Neo4j)
  • 2+ years of experience with deployment and optimization: Kubernetes, Docker, NVIDIA TensorRT/Triton, RAPIDs, Kubeflow, MLflow, Kafka, etc.
  • Live within commuting distance to one of Deloitte's consulting offices...

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