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Sr Machine Learning Engineer Jobs in Miami, FL (NOW HIRING)

Job Title Senior Data Scientist Location Doral, FL 33122 US (Primary) Category Intelligence Job ... Desirable but not required certifications include Google Professional Machine Learning Engineer ...

Machine Learning Tutor

Doral, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Miramar, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Cooper City, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Coral Gables, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Sunrise, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Hialeah, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Miami, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Miami Beach, FL ยท Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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 ...

Senior Forward Deployed Engineer- AWS

Miami, FL ยท On-site

$99K - $137K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ ... Work you'll do As an AWS AI&Data FDE, you will work side by side with senior functional and ...

Showing results 41-60

Sr Machine Learning Engineer information

See Miami, FL salary details

$56.9K

$121K

$175.5K

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

As of Sep 4, 2026, the average yearly pay for sr machine learning engineer in Miami, FL is $121,045.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,900.00 and $137,200.00 per year, depending on experience, location, and employer.

What is a Sr Machine Learning Engineer?

Senior Machine Learning Engineers are experienced professionals who design, develop, and implement machine learning models and systems. They work on complex problems, lead technical projects, and often mentor junior engineers. Their responsibilities include data preprocessing, model selection, algorithm development, and optimizing solutions for scalability and performance. Senior ML Engineers also collaborate closely with data scientists, software engineers, and stakeholders to integrate machine learning into products and services.

What are the key skills and qualifications needed to thrive as a Sr Machine Learning Engineer?

To thrive as a Sr Machine Learning Engineer, you need advanced expertise in machine learning theory, programming (Python, R), data modeling, and a strong background in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms (AWS, GCP), and relevant certifications (like TensorFlow Developer) is highly beneficial. Strong problem-solving skills, effective communication, and the ability to lead and mentor teams set top candidates apart. These skills ensure the ability to design scalable ML solutions, collaborate effectively, and drive impactful business outcomes.

How does a Sr Machine Learning Engineer typically collaborate with data scientists and software engineers within a project team?

Sr Machine Learning Engineers frequently act as a bridge between data scientists, who focus on model development and experimentation, and software engineers, who handle system integration and production deployment. They translate prototype models into scalable, production-ready solutions, ensuring that models are optimized for real-world performance. Collaboration often involves reviewing code, aligning on data pipeline requirements, and participating in regular team meetings to address technical and business objectives. This cross-functional teamwork is essential for delivering reliable machine learning products.

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

AspectSr Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, ML, or related fields; experience with ML frameworksBachelor's/Master's/PhD in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds models, interprets data insights for business
Industry UsageTech, finance, healthcare, e-commerceResearch, marketing, finance, tech

While both roles involve working with data and models, Sr Machine Learning Engineers focus on building and deploying scalable ML systems, whereas Data Scientists primarily analyze data and develop insights. The roles often overlap but differ in technical focus and responsibilities.

What are popular job titles related to Sr Machine Learning Engineer jobs in Miami, FL?

For Sr Machine Learning Engineer jobs in Miami, FL, the most frequently searched job titles are:

What cities near Miami, FL are hiring for Sr Machine Learning Engineer jobs?

Cities near Miami, FL with the most Sr Machine Learning Engineer job openings:

Infographic showing various Sr Machine Learning Engineer job openings in Miami, FL as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $121,045 per year, or $58.2 per hour.

Agentic AI / Machine Learning Architect - Senior Principal (Miami)

Slalom

Miami, FL โ€ข On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 11 days ago


Job description

At Slalom, we co-create modern technology and software products with clients who are accelerating their digital transformation journeys. We blend design, product engineering, analytics, automation, and AI-native delivery to build intelligent products and platforms that can operate safely at enterprise scale. As an AI/ML Architect, youโ€™ll design and deliver production-grade AI systems that combine machine learning, generative AI, agentic workflows, modern data platforms, and cloud-native engineering across AWS, Azure, and Google Cloud. Youโ€™ll partner with clients to shape strategy, define secure and governed architectures, and move AI solutions from experimentation into reliable business operations.

What Youโ€™ll Do
  • Set technical direction for enterprise-scale AI systems spanning data products, retrieval pipelines, model orchestration, agentic workflows, evaluation, deployment, monitoring, optimization, and lifecycle management.
  • Define secure, scalable, cloud-native and hybrid reference architectures across AWS, Azure, and Google Cloud, including modern AI platform services such as Amazon Bedrock, Azure AI Foundry, Google Vertex AI, and enterprise data platforms.
  • Guide applied AI strategy and delivery across generative AI, agentic AI, multimodal AI, advanced RAG, knowledge assistants, prediction, optimization, computer vision, and decision-support use cases.
  • Lead enterprise adoption of production GenAI and agentic AI, including advanced RAG, tool/function calling, structured outputs, workflow orchestration, model routing, prompt and context engineering, memory patterns, and human-in-the-loop controls.
  • Establish AI evaluation, observability, and reliability standards, including offline test sets, automated evals, tracing, hallucination detection, quality scoring, latency/cost monitoring, feedback loops, and regression testing.
  • Champion Responsible AI, AI security, and governance-by-design practices, including explainability, privacy, bias mitigation, guardrails, data protection, threat modeling, access controls, auditability, and compliance alignment.
  • Evaluate emerging models, platforms, frameworks, standards, and deployment patterns, providing executiveโ€‘ready recommendations based on use case fit, enterprise readiness, cost, risk, and operational complexity.
  • Lead and mentor crossโ€‘functional delivery teams of data engineers, AI engineers, ML engineers, software engineers, architects, and consultants, ensuring consistent quality across complex programs.
  • Drive business development through proposals, executive client pitches, solution accelerators, reference architectures, technical points of view, and thought leadership.
  • Develop senior practitioners and practice capability, fostering a culture of continuous learning, engineering discipline, responsible innovation, and practical AI adoption across the AI/ML practice.
  • Help to hire, lead, mentor, and retain a highโ€‘performing, inclusive team of AI/ML engineers, architects, and data scientists. Set clear expectations, provide timely feedback, and create meaningful development and stretch opportunities.
What Youโ€™ll Bring
  • 9+ years of experience implementing ML/AI solutions in production, including classical ML, deep learning, generative AI, or agentic AI systems.
  • 5+ years of experience in professional consulting or IT services, with proven ability to lead complex clientโ€‘facing technical engagements.
  • Proven ability to design and govern production AI systems that combine models, data, retrieval, orchestration, APIs, security controls, observability, operating model, and user experience into an endโ€‘toโ€‘end enterprise architecture.
  • Deep expertise in modern GenAI patterns, including advanced RAG, embeddings, vector and hybrid search, reโ€‘ranking, knowledge graphs, tool/function calling, structured outputs, context engineering, and multimodal inputs.
  • Experience defining agentic AI architecture patterns, including singleโ€‘agent and multiโ€‘agent workflows, supervisor/worker patterns, state and memory management, workflow orchestration, human approval gates, and safe action execution.
  • Proficiency with modern AI engineering frameworks and tools such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, Haystack, CrewAI, Hugging Face, or comparable openโ€‘source and cloudโ€‘native frameworks.
  • Strong programming skills in Python and modern software engineering practices, with familiarity in APIs, eventโ€‘driven patterns, test automation, infrastructure as code, and scalable service design.
  • Proficiency in cloud AI/ML platforms and services such as Amazon Bedrock, AWS SageMaker, Azure AI Foundry, Azure Machine Learning, Google Vertex AI, and related model hosting, retrieval, agent, and evaluation capabilities.
  • Experience with enterprise data and AI ecosystems such as Databricks, Snowflake, Spark, Kafka, dbt, vector databases, lakehouse architectures, and modern data governance patterns.
  • Experience setting standards for MLOps, LLMOps, CI/CD, model and prompt versioning, automated evaluation, observability, containerization, Kubernetes, serverless deployment, and cost/performance optimization.
  • Strong understanding of AI architecture tradeoffs, including model selection, retrieval strategy, latency, accuracy, security, privacy, scalability, cost, vendor lockโ€‘in, and operating model implications.
  • Ability to communicate complex AI concepts to technical and nonโ€‘technical stakeholders, translating architecture choices into business value, delivery risk, governance requirements, and executiveโ€‘level decisions.
  • Experience managing senior delivery teams and shaping enterprise AI/ML roadmaps, reference architectures, implementation backlogs, governance models, and adoption plans for enterprise clients.
  • Strong problemโ€‘solving, critical thinking, and business acumen, with the judgment to distinguish viable production solutions from prototypeโ€‘only patterns and to guide clients through tradeoffs pragmatically.
About Us

Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries partner with clients to coโ€‘create powerful customer experiences, modern ways of working, and meaningful impact.

What sets us apart? We believe work should be challenging and fulfilling, not perfect, but possible. Thatโ€™s why we prioritize purpose, flexibility, connection, and recognition, so our people can thrive and love what they do, most days.

Compensation and Benefits

Slalom prides itself on helping team members thrive in their work and life. As a result, Slalom is proud to invest in benefits that includemeaningful time off and paid holidays, parental leave, 401(k) with a match, a range of choices for highly subsidized health, dental, & vision coverage, adoption and fertility assistance, and short/long-term disability. We also offer yearly $350 reimbursement account for any wellโ€‘beingโ€‘related expenses, as well as discounted home, auto, and pet insurance.

For Boston, New York, Washington D.C.:

The targeted base salary pay range for a Sr. Principal is $215,000 to $275,000.

For Atlanta, Charlotte, Philadelphia, Miami:

The targeted base salary pay range for a Sr. Principal is $200,000 to $250,000.

In addition, individuals may be eligible for an annual discretionary bonus . Actual compensation will depend upon an individualโ€™s skills, experience, qualifications, location, and other relevant factors. The salary pay range is subject to change and may be modified at any time.

Wearecommittedtopaytransparencyandcompliancewithapplicablelaws.Ifyouhavequestionsorconcernsaboutthepayrangeorothercompensationinformationinthisposting,pleasecontactusat: peopleone@slalom.com . Pleasenote,thisrecipientisnotabletosupportrecruitmentinquiriesbeyondthispurpose.

EEO and Accommodations

Slalom is an equal opportunity employer and is committed to attracting, developing and retaining highly qualified talent who empower our innovative teams through unique perspectives and experiences. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteransโ€™ status, or any other characteristic protected by federal, state, or local laws. Slalom will also consider qualified applications with criminal histories, consistent with legal requirements. Slalom welcomes and encourages applications from individuals with disabilities. Reasonable accommodations are available for candidates during all aspects of these selection processes. Please advise the talent acquisition team or contact accomodationrequest@slalom.com if you require accommodations during the interview process.

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