AI/ ML Engineer

Job Role- AI ML Engineer

Location- Mason/ Cincinnati Ohio 

Salary Range- 80k to 85k

Job Description: AI Engineer
As an AI Engineer, you will collaborate closely with senior AI engineers and architects to design, build, test, and deploy AI/ML and GenAI solutions. This role offers hands-on experience in data preparation, model development, evaluation, and integration of AI systems with business applications, providing a strong foundation to build expertise in AI engineering.

Key Responsibilities

Assist in developing and training machine learning and GenAI models under guidance.
Perform data preprocessing, feature engineering, and exploratory data analysis.
Support development of AI applications using Python and standard ML frameworks.
Contribute to evaluating LLM outputs for quality, accuracy, factuality, and bias.
Document model behaviour, datasets, training processes, and versioning.
Collaborate with cross-functional teams for model testing and integration.
Stay updated with emerging AI technologies, tools, and research trends.

Education

Bachelor’s or master’s degree in artificial intelligence, computer science, IT, Data Science, or related fields.

Technical Skills (AI & GenAI Focus)
Programming & ML

Strong programming skills in Python.
Good understanding of NumPy, Pandas, and Scikit-learn.
Basic understanding of TensorFlow or PyTorch.

GenAI & LLM Concepts

Familiarity with LLMs, embeddings, and prompt engineering.
Understanding of GPT, BERT, and generative models such as GANs, VAEs, and Diffusion models.

Tools & Frameworks

Exposure to LangChain, Hugging Face, OpenAI API, Azure OpenAI Service.

Cloud & Advanced Topics

Awareness of Azure AI, AWS Bedrock, and Google Vertex AI.
Basic understanding of RAG pipelines, vector databases (Pinecone, FAISS), agentic AI, and Model Context Protocol (MCP).
Familiarity with CI/CD practices for AI workflows.

Quality, Safety & Ethical AI

Awareness of AI fairness, bias, privacy, and responsible AI principles.
Familiarity with model evaluation metrics and LLM-specific checks such as hallucination and factuality assessments.

Soft Skills

Curiosity and strong learning mindset.
Good communication skills and ability to work with cross-functional teams.
Problem-solving ability with a structured approach and willingness to iterate on prototypes.

Nice-to-Have (Preferred)

Certifications such as Azure AI Engineer Associate, AWS Machine Learning Specialty, Google Professional ML Engineer, or Databricks badges.
Internship or academic project experience in AI/ML or GenAI.