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Senior Machine Learning Engineer Jobs in Winter Haven, FL

... and machine learning. * Translate data and quantitative analysis into actionable recommendations for Business Development, Marketing, and senior leadership. * Extract, transform, analyze, and ...

Senior AI / Data Engineer

Celebration, FL

$93K - $127K/yr

The Data Engineer III role, will report to the Senior Manager, Data Services. About The Role & Team ... machine learning * Uphold design standards and quality assurance protocols for the development of ...

Technology - Sr. Engineer

Celebration, FL ยท On-site

$95K - $131K/yr

... learning. We offer quality career resources, training, certifications, development opportunities ... UnitedHealthcare creates and publishes the Transparency in Coverage Machine-Readable Files on ...

Technology - Sr. Engineer

Celebration, FL ยท On-site

$125 - $150/hr

Technology - Sr. Engineer Location: Celebration, Florida (Onsite) Role Overview The Senior Platform ... learning. We offer quality career resources, training, certifications, development opportunities ...

... science and machine learning solutions that drive business performance, enhance customer ... Ph.D. degree in data science, computer science, statistics, neuroscience, engineering, mathematics ...

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Showing results 1-20

Senior Machine Learning Engineer information

See Winter Haven, FL salary details

$52K

$110.7K

$160.5K

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

As of Sep 8, 2026, the average yearly pay for senior machine learning engineer in Winter Haven, FL is $110,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,400.00 and $125,500.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What job categories do people searching Senior Machine Learning Engineer jobs in Winter Haven, FL look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Winter Haven, FL are:

What cities near Winter Haven, FL are hiring for Senior Machine Learning Engineer jobs?

Cities near Winter Haven, FL with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Winter Haven, FL as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $110,670 per year, or $53.2 per hour.

Senior Principal Data Scientist / AI-ML SME (Analytic Superiority) (Fort Meade)

Via Logic LLC

Fort Meade, FL โ€ข On-site

$154K - $278K/yr

Full-time

Posted 20 days ago


Job description

Mission Overview

The Leidos Intel Sector is looking for a premier AI/ML Subject Matter Expert (SME) to serve as a Technical Closer for our COSS 3.0 program supporting USCYBERCOM and the Cyber National Mission Force (CNMF) at Fort Meade, MD. In this elite role, you will architect and engineer the crossโ€‘platform AI frameworks required to achieve absolute analytic superiority.

You will compress both defensive cyber operations (identifying network vulnerabilities and gaps) and offensive operations (vulnerability discovery and automated targeting) from days down to minutes. As a Technical Closer, you will mentor senior technologists by example-working fingers-on-keyboard to solve the command's most complex technical roadblocks and push productionโ€‘grade AI directly into multiโ€‘cloud, hybrid, and airโ€‘gapped mission enclaves.

Core Technical Requirements
  • Platformโ€‘Agnostic Infrastructure & MLOps: Architect, deploy, and scale distributed AI workloads across any environment required, including AWS SageMaker, Google Vertex AI, Azure Government, and bareโ€‘metal, airโ€‘gapped server racks.
  • Agentic AI & Cyber Automation: Deploy and optimize tools like LangGraph, CrewAI, or AutoGPT to automate cyber threat identification and offensive target generation at wire speed.
  • Lowโ€‘Level Model Engineering & Optimization: Fineโ€‘tune openโ€‘source large language models (e.g., Llama 3, Mistral) inside secure enclaves using PyTorch or TensorFlow. Utilize NVIDIA TensorRT, Triton Inference Server, vLLM, and quantization libraries (bitsandbytes) to compress models for highโ€‘throughput execution under strict hardware constraints.
  • Advanced RAG Architectures: Direct the engineering of enterprise Retrievalโ€‘Augmented Generation (RAG) stacks using LangChain paired with highโ€‘performance vector databases like Milvus, Qdrant, or Pinecone.
  • Autonomous Cyber Integration: Connect intelligent agents directly into security orchestration platforms (e.g., Palo Alto Cortex XSIAM/XSOAR) to trigger automated network defense actions and ingest massive, realโ€‘time PCAP and telemetry streams via Apache Kafka/Spark.
  • Polyglot Engineering: Demonstrate engineering mastery in Python, Go, Rust, and C/C++ to build ultraโ€‘fast cyber tools, write optimized GPU kernels, and interface with distributed frameworks like Ray.
Mission & Domain Expertise
  • Dualโ€‘Spectrum Operations: Proven capability to support both Defensive Cyber Operations (DCO) (log parsing, behavioral threat hunting, anomaly detection) and Offensive Cyber Operations (OCO) (automated vulnerability discovery, exploit generation, payload optimization).
  • Mission Platform Orchestration: Experience integrating custom AI/ML pipelines into unified mission systems and highโ€‘value data streams found across Project Maven, Palantir Foundry, and tactical command frameworks.
Required Experience & Background
  • Total Technical Experience: 15+ years of handsโ€‘on experience in software engineering, data science, or distributed systems.
  • Core AI/ML Focus: 5+ years of specialized experience in Machine Learning Engineering, deep learning, or LLM optimization.
  • DoD/IC Ecosystem: 3-5 years working within the DoD/IC cyber ecosystem, specifically building tools that map vulnerabilities or accelerate targeting cycles.
  • Clearance: Active TS/SCI with Polygraph.
  • Work Location: Onโ€‘site at Fort Meade, MD (SCIF environment).
Preferred Certifications & Military Equivalency
  • Industry Certifications: Google Cloud Professional Machine Learning Engineer, AWS Certified Machine Learning - Specialty, or NVIDIA Generative AI/LLM Associate.
  • Cyber Mission Force (CMF) Equivalency: Prior certification as a CMF Exploitation Analyst (EA), Digital Network Analyst (DNA), or specialized technical experience as an Army 17A/170A, Navy 181X, or Air Force 17D/17S.
Educational Background
  • Primary Requirement: Master's Degree or PhD in Data Science, Artificial Intelligence, Computer Science, Mathematics, or a related quantitative field. Additional years of experience may be considered in lieu of a degree.
Pay Range

Pay Range $154,050.00 - $278,475.00

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.

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