Junior AI Engineer

Job Title: Junior AI Engineer

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About Us

Soothsayer Analytics is a global AI & Data Science consultancy headquartered in Detroit, with a thriving delivery center in Hyderabad. We design and deploy end-to-end custom Machine Learning & GenAI solutions—spanning predictive analytics, optimization, NLP, computer vision, and enterprise-scale AI platforms—that help leading enterprises forecast, automate, and gain a competitive edge.

This is a unique opportunity to begin your AI career by working on cutting-edge GenAI, ML, and data-driven projects across industries.

Job Overview

Junior AI Engineer

Key Responsibilities:

Model Development & Support

• Assist in building ML models (classification, regression, clustering, forecasting).
• Contribute to fine-tuning and prompt engineering for LLMs (GPT, LLaMA, etc.).
• Experiment with vector databases and RAG pipelines for GenAI applications.

Data Preparation & Engineering

• Work with structured/unstructured datasets for ML training.
• Perform data cleaning, feature engineering, and basic pipeline development.

MLOps & Deployment (Learning Role)

• Support containerization and deployment of models using Docker/Kubernetes.
• Learn to implement CI/CD pipelines for ML workflows.

Collaboration & Learning

• Work under guidance of senior engineers and data scientists.
• Document experiments and present results to technical and business stakeholders.

Required Skills & Qualifications

• Education:

  Bachelor’s in Computer Science, AI, Data Science, or related field.

• Experience:

  1–2 years (including internships, academic projects, or full-time roles).

• Technical Skills:

• Programming:

  Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow).

• ML Basics:

  Regression, classification, clustering, time-series.

• GenAI/LLMs:

  Prompt engineering, LangChain basics, RAG concepts.

• Databases:

  SQL (basic), exposure to NoSQL/vector DBs (Pinecone, FAISS).

• MLOps Exposure:

  Docker, Git, basic CI/CD knowledge.
• Bonus: Knowledge of

  vision models, transformers, or cloud AI services

  (AWS Sagemaker, Azure ML, GCP Vertex AI).

Please submit skills matrix in tabular format having the following columns:

Skill, Details, Skills Last Used, Experience (months), Self-Rating (0–10)

Python (pandas, sklearn, PyTorch/TensorFlow)

ML Basics (Regression, Clustering, etc.)

GenAI/LLMs (Prompting, LangChain, etc.)

SQL / NoSQL

Vector Databases (FAISS, Pinecone, pgvector)

MLOps Tools (Docker, Git, CI/CD)

Cloud AI Platforms (AWS/Azure/GCP)

Instructions for Candidates:

1. Provide a detailed resume highlighting

   academic/ industry projects in ML and AI

   .
2. Fill out the above

   skills matrix

   with accurate details and self-ratings.