Junior AI Engineer

SFE; Edison (NE); On-site; USD 85,000 - 95,000; Full time

Job summary

SFE is seeking an Entry Level Python AI Data Scientist Engineer to join our team for a client project with TCS. The role targets candidates with 0-2+ years of experience and onsite work across Milford OH, Edison NJ, and Santa Clara CA.

You will work on Python-based AI/ML projects, including NLP/chatbots, prompt engineering, and data processing involving embeddings and vector databases. Collaboration in Agile teams and attention to quality are essential.

Qualifications

• Proficiency in Python and software engineering fundamentals.
• Experience with NLP or chatbots.
• Experience with prompt engineering and few-shot prompts.
• Familiarity with embedding models and vector databases.
• Experience building RESTful APIs and microservices.
• Strong debugging and problem-solving skills.
• Comfortable working in Agile teams.
• Attention to data handling and edge-case testing.
• Awareness of bias and confidentiality considerations.
• Quick learner for domain adaptation.

Skills

Python

Java

JavaScript

C#

Unit testing

Git

NLP

Prompt engineering

RAG

Embeddings

APIs

Job description

Job Details:-

Job Title: Entry Level Python AI Data Scientist Engineer

Experience Required:- 0-2+ Years

Location: Milford OH ,Edison NJ and Santa Clara CA Onsite

Duration: Fulltime Hire with Client TCS

Salary Range: $85,000 - $95,000 a year

Programming & Software Engineering: Expertise in Python (and optionally Java, JavaScript, or C#), unit testing, and version control (Git).

AI/ML Knowledge: Solid grasp of machine learning and AI concepts, model behavior, and experience with NLP or chatbots.

Prompt Engineering: Experience crafting and iterating prompts, including few-shot examples and output formatting techniques.

RAG and Data Handling: Familiarity with embedding models, vector databases, and unstructured data processing.

API and Integration Skills: Building and consuming RESTful APIs, microservices, and handling JSON/XML data formats.

Data Structures & Algorithms: Knowledge of lists, dictionaries, trees/graphs, and their application in efficient agent design.

Debugging & Problem-Solving: Strong troubleshooting abilities to distinguish between model and code issues.

Agile and Collaborative Mindset: Comfortable working in sprints, collaborating across teams, and communicating technical needs.

Domain Adaptability: Ability to quickly learn new industry concepts for tailored agent solutions.

Attention to Detail & Quality: Consideration of edge cases, proper data handling, and thorough testing.

Ethical Awareness: Recognize bias, confidentiality issues, and flag questionable requests.