Data Scientist

Kavaliro; Florida; On-site; USD 140,000 - 200,000; Full time

Job summary

Kavaliro is seeking a Senior AI/ML Engineer to lead the design, development, deployment, and optimization of advanced ML/AI solutions across the full lifecycle, from problem framing and data ingestion to model deployment and monitoring.

You will collaborate with engineering, analytics, product, and leadership to build scalable AI systems that drive business outcomes, applying MLOps, CI/CD, and cloud-native practices.

Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, Statistics, Mathematics, Engineering, or a related technical discipline.
• 5+ years of professional experience in machine learning, AI engineering, software engineering, or data science with production deployments.
• 3+ years of experience building and deploying machine learning solutions in commercial environments.
• Advanced Python programming skills with experience developing, training, testing, and deploying machine learning models.
• Strong SQL expertise for data extraction, transformation, and analysis.
• Experience building end-to-end ML systems from data ingestion through production serving.
• Strong understanding of supervised, unsupervised, and deep learning methodologies.
• Experience deploying solutions within cloud environments such as AWS, Azure, or Google Cloud Platform.
• Familiarity with modern data platforms including Snowflake, BigQuery, Redshift, SQL Server, or equivalent technologies.
• Demonstrated experience owning AI solutions in production environments including monitoring, optimization, and operational support.
• Strong problem-solving, systems-thinking, and analytical skills.
• Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences.
• Ability to manage multiple priorities in a fast-paced environment.
• Must be available to start onsite and travel occasionally as required.

Responsibilities

• Design, build, train, evaluate, and deploy machine learning and AI solutions for complex business challenges.
• Translate ambiguous requirements into scalable AI‑driven systems and technical architectures.
• Develop predictive models, classification systems, recommendation engines, personalization frameworks, and generative AI applications.
• Fine‑tune, evaluate, and optimize Large Language Models (LLMs) and other advanced AI architectures as appropriate.
• Build robust, scalable machine learning pipelines from data ingestion through production deployment.
• Implement CI/CD processes, automated testing, model validation, monitoring, and retraining workflows.
• Develop production‑ready APIs and services that integrate AI capabilities into enterprise applications.
• Maintain model lifecycle management, performance monitoring, and continuous optimization processes.
• Ensure systems meet security, scalability, reliability, and performance standards.
• Document architectures, models, deployment procedures, and engineering standards to support maintainability and knowledge sharing.
• Collaborate with cross‑functional stakeholders to communicate technical solutions and recommendations.
• Stay current with emerging AI technologies, frameworks, and industry best practices.
• Contribute to AI strategy, platform selection, and architectural decision‑making.

Skills

Python

SQL

ML deployment

End-to-end ML systems

Communication

Problem solving

Systems thinking

Team collaboration

Education

Bachelor's degree in Computer Science, AI, Data Science, Statistics, Mathematics, Engineering

Master's degree or higher in Computer Science, AI, ML, Statistics, Mathematics, or related field

Tools

AWS

Azure

Google Cloud Platform

Snowflake

BigQuery

Redshift

MLflow

Airflow

SageMaker

Kubeflow

Databricks

Job description

Job Description

We are seeking a highly skilled Senior AI/ML Engineer to lead the design, development, deployment, and optimization of advanced machine learning and artificial intelligence solutions. This role is ideal for a hands‑on technical professional who thrives at the intersection of machine learning, software engineering, cloud infrastructure, and MLOps. As a key member of the team, you will own the full AI development lifecycle, from problem definition and data ingestion through model development, evaluation, deployment, monitoring, and continuous improvement. You will work closely with engineering, analytics, product, and leadership teams to build scalable AI systems that drive innovation and business outcomes.

Key Responsibilities

AI & Machine Learning Development

• Design, build, train, evaluate, and deploy machine learning and AI solutions for complex business challenges.
• Translate ambiguous requirements into scalable AI‑driven systems and technical architectures.
• Develop predictive models, classification systems, recommendation engines, personalization frameworks, and generative AI applications.
• Fine‑tune, evaluate, and optimize Large Language Models (LLMs) and other advanced AI architectures as appropriate.

Production Engineering & MLOps

• Build robust, scalable machine learning pipelines from data ingestion through production deployment.
• Implement CI/CD processes, automated testing, model validation, monitoring, and retraining workflows.
• Develop production‑ready APIs and services that integrate AI capabilities into enterprise applications.
• Maintain model lifecycle management, performance monitoring, and continuous optimization processes.
• Ensure systems meet security, scalability, reliability, and performance standards.

Technical Leadership

• Document architectures, models, deployment procedures, and engineering standards to support maintainability and knowledge sharing.
• Collaborate with cross‑functional stakeholders to communicate technical solutions and recommendations.
• Stay current with emerging AI technologies, frameworks, and industry best practices.
• Contribute to AI strategy, platform selection, and architectural decision‑making.

Required Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related technical discipline.
• 5+ years of professional experience in machine learning, AI engineering, software engineering, or data science with production deployments.
• 3+ years of experience building and deploying machine learning solutions in commercial environments.
• Advanced Python programming skills with experience developing, training, testing, and deploying machine learning models.
• Strong SQL expertise for data extraction, transformation, and analysis.
• Experience building end‑to‑end ML systems from data ingestion through production serving.
• Strong understanding of supervised, unsupervised, and deep learning methodologies.
• Experience deploying solutions within cloud environments such as AWS, Azure, or Google Cloud Platform.
• Familiarity with modern data platforms including Snowflake, BigQuery, Redshift, SQL Server, or equivalent technologies.
• Demonstrated experience owning AI solutions in production environments including monitoring, optimization, and operational support.
• Strong problem‑solving, systems‑thinking, and analytical skills.
• Excellent communication skills with the ability to explain technical concepts to both technical and non‑technical audiences.
• Ability to manage multiple priorities in a fast‑paced environment.
• Must be available to start onsite and travel occasionally as required.

Preferred Qualifications

• Master's degree or higher in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, or a related field.
• Experience with MLOps platforms and orchestration tools such as MLflow, Airflow, SageMaker, Kubeflow, Databricks, or similar technologies.
• Hands‑on experience with Generative AI, Large Language Models (LLMs), Retrieval‑Augmented Generation (RAG), vector databases, prompt engineering, and AI agents.
• Experience working with Hugging Face, Bedrock, Azure AI Studio, OpenAI APIs, LangChain, LlamaIndex, or equivalent AI frameworks.
• Knowledge of transformer architectures, NLP, embeddings, recommendation systems, and personalization engines.
• Experience developing scalable AI applications using containerization and orchestration technologies such as Docker and Kubernetes.
• Strong understanding of cloud‑native AI infrastructure and distributed computing environments.
• Experience designing AI governance, model monitoring, evaluation frameworks, and responsible AI practices.
• Proven ability to influence technical strategy and architectural decisions for AI platforms and infrastructure.

Kavaliro provides Equal Employment Opportunities to all employees and applicants. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Kavaliro is committed to the full inclusion of all qualified individuals. In keeping with our commitment, Kavaliro will take the steps to assure that people with disabilities are provided reasonable accommodations. Accordingly, if reasonable accommodation is required to fully participate in the job application or interview process, to perform the essential functions of the position, and/or to receive all other benefits and privileges of employment, please respond to this posting to connect with a company representative.

Remote