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Machine Learning Ai Jobs (NOW HIRING)

Team Velocity Marketing

$160K - $190K/yr

Senior Data Scientist - Machine Learning & AI Senior Data Scientist - Machine Learning & AI Remote | Full-Time | $160,000-$190,000 Team Velocity is seeking a Senior Data Scientist to develop and ...

Workiva Inc.

## Manager of Machine Learning - AI Modeling and OperationApplylocations: USA - Remotetime type: Full timeposted on: Posted Todayjob requisition id: R12166Join our team at Workiva as an **Manager of ...

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Machine Learning Ai information

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$25.5K

$42.6K

$88K

How much do machine learning ai jobs pay per year?

As of Sep 10, 2026, the average yearly pay for machine learning ai in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What is a machine learning AI?

A Machine Learning AI specialist is a professional who develops algorithms and models that enable computers to learn from and make predictions or decisions based on data. They work with large datasets, train and evaluate machine learning models, and often collaborate with software engineers and data scientists to integrate AI solutions into products and services. Their work is crucial in fields like natural language processing, computer vision, and predictive analytics, helping organizations automate tasks, gain insights, and improve efficiency.

What are the key skills and qualifications needed to thrive as a machine learning AI?

To thrive as a Machine Learning AI Engineer, you need a strong background in mathematics, statistics, programming (typically Python), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow and PyTorch, as well as cloud platforms and data processing tools, is essential, and certifications in these areas can be advantageous. Strong problem-solving, communication, and collaboration skills help you effectively translate business needs into technical solutions and work well within multidisciplinary teams. These skills ensure you can develop robust AI models that address real-world challenges and deliver meaningful business impact.

What are some common challenges faced when collaborating with cross-functional teams as a machine learning AI?

As a Machine Learning AI professional, you’ll often collaborate with data engineers, software developers, and product managers. A common challenge is bridging the gap between complex AI models and practical business requirements, ensuring your solutions are both technically sound and aligned with user needs. Effective communication is key, as you’ll need to explain technical concepts to non-technical stakeholders and adapt your models based on feedback. Building trust and fostering a collaborative environment will help ensure successful project outcomes and foster continual learning.

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

AspectMachine Learning AiData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; experience with programming and algorithmsDegree in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentDeveloping algorithms, training models, deploying AI systemsAnalyzing data, creating reports, interpreting results
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, tech firms

Machine Learning Ai focuses on developing and deploying AI algorithms and models, while Data Scientists analyze and interpret data to inform business decisions. Both roles often collaborate but have distinct focuses within the data and AI ecosystem.

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Machine Learning Ai jobs near you
Infographic showing various Machine Learning Ai job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Sr. Machine Learning/AI Engineer

Cornelius, NC • On-site

Financial Independence Group
Insurance Services • 51 - 200 employees
Learn more about Financial Independence Groupexternal

$96K - $132K/yr

Full-time

Re-posted 17 days ago

Job description

Job Summary:
Financial Independence Group (FIG) is one of the nation’s largest Finance and Insurance Marketing Organizations, focusing on expanding financial products and services. They are seeking a Senior Machine Learning/AI Engineer to architect and operationalize intelligent systems, develop machine learning models, and collaborate with cross-functional teams to drive organizational efficiency.
Responsibilities:
• Design, build, and deploy machine learning models and AI systems at scale.
• Develop LLM‑powered applications, including RAG pipelines, agent workflows, and automated decision‑support tools.
• Collaborate with cross‑functional partners to translate business needs into technical AI solutions.
• Work closely with data engineering to ensure strong data availability, quality, and ML readiness.
• Mentor engineers and analysts, guiding best practices in MLOps, model development, and responsible AI.
• Implement monitoring, observability, and model governance frameworks.
• Maintain high standards for security, safety, and compliance aligned with FIG’s AI governance.
• Evaluate new models, tools, and frameworks to continuously expand FIG’s AI capabilities.
• Present recommendations, insights, and solution designs to technical and non‑technical stakeholders.
Qualifications:
Required:
• Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow, scikit‑learn).
• Experience building and deploying machine learning models into production environments.
• Hands‑on experience working with large language models (LLMs), transformers, vector databases, embeddings, and retrieval‑augmented generation (RAG).
• Ability to design end‑to‑end AI pipelines from data ingestion and feature engineering to training, evaluation, deployment, and monitoring.
• Familiarity with prompt engineering, fine‑tuning, and model optimization techniques.
• Experience implementing MLOps workflows and tools (MLflow, Databricks, Weights & Biases, SageMaker, AgentCore or similar).
• Knowledge of agent frameworks (Strands, LangChain, Semantic Kernel, CrewAI, AutoGen).
• Knowledge of cloud technologies (AWS preferred), containerization and orchestration.
• Strong SQL skills and comfort working with modern data platforms (e.g., Snowflake, Redshift, BigQuery, Synapse).
• Experience deploying APIs, microservices, and distributed systems.
• Ability to evaluate model performance, identify failure modes, and optimize for accuracy, fairness, and reliability.
• Strong critical‑thinking skills paired with creativity in designing AI‑driven solutions.
• Experience conducting exploratory analysis, model experimentation, and error analysis.
• Ability to balance technical excellence with practical business impact.
• Ability to translate business needs into scalable AI solutions.
• Experience partnering with cross‑functional teams across engineering, data, operations, and leadership.
• Strong communication skills with the ability to present complex concepts clearly.
• Ability to mentor, guide, and influence teammates and stakeholders.
Preferred:
• Experience in financial services, insurance, wealth management, or other regulated industries.
• Prior involvement in AI governance, responsible AI frameworks, or risk assessments.
• Experience contributing to data governance, metadata management, or model lineage documentation.
• Familiarity with experimentation frameworks, A/B testing, or statistical modeling.
• Working knowledge of reinforcement learning, recommendation systems, or advanced NLP techniques.
Company:
Welcome to Financial Independence Group, or FIG Marketing. Founded in 1976, the company is headquartered in Cornelius, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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