Working Hours : Full Time

Locations : Hyderabad

Experience : 6 –10 years

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About The Role

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

Join us to tackle high-impact, cross-industry projects where your ideas move rapidly from concept to production, shaping the future of data-driven decision-making.

We seek a Senior AI Scientist with strong ML fundamentals and data engineering expertise to lead the development of scalable AI/LLM solutions. You will design, fine-tune, and deploy models (e.g., LLMs, RAG architectures) while ensuring robust data pipelines and MLOps practices.

Key Responsibilities

AI/LLM Development:

Fine-tune and optimize LLMs (e.g., GPT, Llama) and traditional ML models for production.
Implement retrieval-augmented generation (RAG), vector databases, and orchestration tools (e.g., LangChain).

Data Engineering:

Build scalable data pipelines for unstructured/text data (e.g., Spark, Kafka, Airflow).
Optimize storage/retrieval for embeddings (e.g., pgvector, Pinecone).

MLOps & Deployment:

Containerize models (Docker) and deploy on cloud (AWS/Azure/GCP) using Kubernetes.
Design CI/CD pipelines for LLM workflows (experiment tracking, monitoring).

Collaboration:

Work with DevOps to optimize latency/cost trade-offs for LLM APIs.
Mentor junior team members on ML engineering best practices.

Required Skills & Qualifications

Education: MS/PhD in CS/AI/Data Science (or equivalent experience).
Experience: 6+ years in ML + data engineering, with 2+ years in LLM/GenAI projects.

Skills Matrix

Candidates must submit a detailed resume and fill out the following matrix:

Skill

Details

Skills Last Used

Experience (months)

Self-Rating (0–10)

Python

ML

SQL/NoSQL

Apache Spark/Kafka

LLM Frameworks (LangChain, etc.)

MLOps (Docker/K8s)

Cloud (AWS/Azure/GCP)

Vector Databases (Pinecone, pgvector)

Instructions For Candidates

Provide a detailed resume highlighting projects related to LLMs, data engineering, and MLOps.
Fill out the matrix above with accurate dates, experience duration, and self-ratings.

Senior AI Scientist (ML + Data Engineering Focus)