Identity AI​/ML Engineer

This role is for an Identity AI / ML Engineer in Columbus, OH, with a contract length of 6+ months, offering a competitive pay rate. Requires strong Python, AI/ML, and data engineering skills, with local candidates preferred for this fully on-site position.

United States

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Unknown

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January 28, 2026

More than 6 months

Remote

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Indiana

Python Developer {AI/ML & Data Engineering experience needed}

Columbus - OH

Fully On-Site from day one.

Local candidates preferred.

Contract (Minimum 06+ Months)

Jr. Role :
Foundational experience in AI/ML and data engineering. Candidate will support data pipelines, assist in ML model development, and work closely with senior engineers to deliver scalable data-driven solutions.

Sr. Role :
Strong experience in AI/ML and data engineering to design, build, and optimize scalable data platforms and machine learning solutions.

Lead Role :
Lead Python Developer to drive AI/ML and data engineering initiatives, lead technical teams, and architect enterprise-scale data and machine learning platforms.

Develop and maintain Python-based applications and data pipelines.

Assist in building and training ML models under guidance.

Work with structured and unstructured data sources.

Perform data cleaning, transformation, and validation.

Support ETL processes and basic cloud deployments.

Collaborate with cross-functional teams (Data, AI, Product).

Design and develop scalable Python applications and data pipelines.

Build, train, and deploy ML models in production environments.

Optimize data workflows for performance and reliability.

Work with big data technologies and distributed systems.

Collaborate with data scientists and architects on solution design.

Ensure code quality, security, and best practices.

Lead end-to-end design and delivery of AI/ML and data engineering solutions.

Architect scalable, secure, and high-performance data platforms.

Guide and mentor junior and senior developers.

Define best practices, coding standards, and architecture guidelines.

Work closely with stakeholders to translate business requirements into technical solutions.

Oversee ML model lifecycle, deployment, and monitoring.

Strong Python programming fundamentals.

Basic understanding of ML concepts (regression, classification, clustering).

Experience with Pandas, Num Py, Scikit-learn.

Knowledge of SQL and databases.

Exposure to ETL tools or data pipelines.

Familiarity with cloud platforms (AWS/Azure/Google Cloud Platform basic).

Advanced Python development experience.

Strong hands‑on experience with ML frameworks (Scikit-learn, Tensor Flow, PyTorch).

Data engineering experience using Spark/PySpark.

Strong SQL and No

SQL database knowledge.

Experience with ETL/ELT pipelines.

Hands‑on cloud experience (AWS, Azure, or Google Cloud Platform).

CI/CD and version control (Git).

Expert‑level Python development.

Strong architecture experience in AI/ML systems.

Deep data engineering expertise (Spark, PySpark, Hadoop, Kafka).

Production ML deployment and MLOps experience.

Strong cloud architecture experience (AWS, Azure, Google Cloud Platform).

Experience leading teams and technical decision‑making.

Exposure to PySpark or Spark.

Basic knowledge of Tensor Flow or PyTorch.

Understanding of REST APIs and Git.

Experience with MLOps tools (MLflow, Kubeflow, Sage Maker).

Knowledge of Kafka or real‑time data streaming.

Exposure to containerization (Docker, Kubernetes).

Experience with GenAI, LLMs, and vector databases.

Exposure to Snowflake, Databricks, or Big Query.

Strong communication and stakeholder management skills.

For applications and inquiries, contact: