AI Engineer
Role - AI Engineer
Location: United States (Candidates should be open and flexible to relocate/work across different states based on project needs)
About the Role
We are looking for a passionate and driven AI Engineer to join our growing AI team in the United States. In this role, you will collaborate with experienced engineers and architects to design, build, and deploy innovative AI/ML and Generative AI solutions.
This is an exciting opportunity to gain hands-on experience across the entire AI lifecycle—from data preparation and model development to evaluation and real-world deployment—while working on cutting-edge technologies such as LLMs, RAG pipelines, and agentic AI systems.
Key Responsibilities
- Assist in building, training, and fine-tuning machine learning and Generative AI models
- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA)
- Develop AI-powered applications using Python and common ML frameworks
- Evaluate LLM outputs for accuracy, quality, factuality, and bias
- Document model behavior, dataset usage, and training workflows for reproducibility
- Collaborate with cross-functional teams (product, engineering, data) for testing and integration
- Stay up to date with the latest AI advancements, tools, and research trends
Education
- Bachelor’s or Master’s degree in Artificial Intelligence, Computer Science, IT, Data Science, or related fields
Technical Skills
Programming & Machine Learning
- Strong proficiency in Python
- Hands-on experience with NumPy, Pandas, Scikit-learn
- Basic understanding of TensorFlow or PyTorch
GenAI & LLM Foundations
- Familiarity with LLMs, embeddings, and prompt engineering
- Understanding of GPT, BERT, and generative models such as GANs, VAEs, Diffusion models
Tools & Frameworks
- Exposure to LangChain, Hugging Face, OpenAI APIs, Azure OpenAI Service
Cloud & Advanced AI Concepts
- Awareness of Azure AI, AWS Bedrock, Google Vertex AI
- Basic understanding of RAG pipelines, vector databases (Pinecone, FAISS)
- Knowledge of Agentic AI and Model Context Protocol (MCP) fundamentals
- Familiarity with CI/CD practices for AI workflows
Responsible AI & Quality
- Awareness of AI fairness, bias, privacy, and responsible AI principles
- Understanding of model evaluation metrics and LLM-specific challenges such as hallucination detection and factual accuracy
Soft Skills
- Strong curiosity and eagerness to learn
- Effective communication and collaboration skills
- Analytical thinking with a structured problem-solving approach
- Willingness to experiment, iterate, and innovate
Nice-to-Have (Preferred)
- Certifications such as:
- Azure AI Engineer Associate
- AWS Machine Learning Specialty
- Google Professional ML Engineer
- Databricks certifications
- Internship or academic project experience in AI/ML or Generative AI
Why Join Us
- Work on cutting-edge AI and GenAI initiatives
- Gain mentorship from experienced AI architects and engineers
- Exposure to real-world, large-scale AI deployments
- Dynamic, innovative, and collaborative work environment across the U.S.