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AI Engineer Trainee

Tata Consultancy Services
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Role - AI Engineer (Entry Level)

Location - Dallas, TX

Job Type - Full time

 

 

As an AI Engineer Trainee, you will work with senior AI engineers and architects to build, test, and deploy AI/ML and GenAI solutions. The role provides hands-on exposure to real-world AI workflows, including data preparation, model development, evaluation, and integration with business applications.

 

 

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 ML frameworks.

• Contribute to evaluation of AI/LLM outputs for quality, accuracy, factuality, and bias.

• Document model behaviour, training process, datasets used, and versioning.

• Collaborate with cross-functional teams for model testing and integration.

• Stay updated with emerging AI technologies, research, and tools.

Education

• Bachelor’s or Master’s degree in Computer Science, IT, Data Science, or related fields

 

Technical Skills (AI & GenAI Focus)

• Strong skills in Python

• Strong foundation in Python and libraries such as NumPy, Pandas, Scikit-learn.

• Basic understanding of deep learning frameworks (TensorFlow, PyTorch).

• Familiarity with GenAI concepts (LLMs, embeddings, prompt engineering)

• Core Concepts: LLMs (GPT, BERT), Generative Models (GANs, VAEs, Diffusion).

• Tools & Frameworks: LangChain, Hugging Face, OpenAI API, Azure OpenAI Service.

• Cloud Platforms: Azure AI, AWS Bedrock, GCP Vertex AI.

• Advanced Topics: RAG pipelines, Vector DBs (Pinecone, FAISS), Prompt Engineering, Agentic AI, Model Context Protocol (MCP)

• Development Skills: Python, TensorFlow, PyTorch, CI/CD for AI pipelines.

 

Quality, Safety & Ethics (AI)

• Awareness of AI fairness, bias, privacy, and responsible AI practices.

• Familiarity with model evaluation metrics for classification/regression and LLM-specific metrics (quality, hallucination checks, factuality).

Soft Skills

Education

• Bachelor’s or Master’s degree in Computer Science, IT, Data Science, or related fields

 

Technical Skills (AI & GenAI Focus)

• Strong skills in Python

• Strong foundation in Python and libraries such as NumPy, Pandas, Scikit-learn.

• Basic understanding of deep learning frameworks (TensorFlow, PyTorch).

• Familiarity with GenAI concepts (LLMs, embeddings, prompt engineering)

• Core Concepts: LLMs (GPT, BERT), Generative Models (GANs, VAEs, Diffusion).

• Tools & Frameworks: LangChain, Hugging Face, OpenAI API, Azure OpenAI Service.

• Cloud Platforms: Azure AI, AWS Bedrock, GCP Vertex AI.

• Advanced Topics: RAG pipelines, Vector DBs (Pinecone, FAISS), Prompt Engineering, Agentic AI, Model Context Protocol (MCP)

• Development Skills: Python, TensorFlow, PyTorch, CI/CD for AI pipelines.

 

Quality, Safety & Ethics (AI)

• Awareness of AI fairness, bias, privacy, and responsible AI practices.

• Familiarity with model evaluation metrics for classification/regression and LLM-specific metrics (quality, hallucination checks, factuality).

Soft Skills

• Curiosity and learning mindset: eagerness to explore new AI frameworks and stay current with advancements.

• Collaboration & communication: ability to translate technical insights for non-technical stakeholders.

• Problem-solving: structured approach to framing problems, building prototypes, and iterating quickly.

Nice-to-Have (Preferred)

• Certifications (e.g., Azure AI Engineer Associate, AWS Machine Learning Specialty, Google Professional ML Engineer) or Databricks Lakehouse badges.

 

 

Salary - $60K - $70K Per Annum + Benefits