AI research engineer Intern

Job Title:

Reporting to:

Location:

Engagement:

1. Why this role exists

Stratsyns cloud-native Enterprise Intelligence & Management Suite

To keep pushing that frontier, we need sharp, curious minds who can translate cutting-edge research into production-grade capabilities for this suite. This internship is our talent-funnel into future Research Engineer and Product Scientist roles.

2. What youll do (core responsibilities)

30 %Rapid Prototyping & Experimentation

3. What you will learn / outcomes to achieve

• Master the end-to-end research workflow: literature review ? hypothesis ? prototype ? validation ? deployment shadow.
• Deliver

  one

  peer-review-quality technical report

  and

  two

  production-grade proof-of-concepts for the Suite.
• Achieve a measurable impact (e.g., 8-10 % forecasting-accuracy lift or 30 % latency reduction) on a live micro-service.

4. Minimum qualifications (freshers welcome)

• B.E./B.Tech/M.Sc./M.Tech in CS, Data Science, Statistics, EE, or related (2024-2026 pass-out).
• Fluency in Python and at least one deep-learning framework (PyTorch preferred).
• Solid grasp of linear algebra, probability, optimization, and algorithms.
• Hands-on academic or personal projects in NLP, CV, time-series, or RL (GitHub links highly valued).

5. Preferred extras

• Publications or Kaggle/ML-competition record.
• Experience with distributed training (GPU clusters, Ray, Lightning) and experiment-tracking tools.
• Familiarity with MLOps (Docker, CI/CD, Kubernetes) or data-centric AI.
• Domain knowledge in supply-chain, fintech, climate, or marketing analytics.

6. Key attributes & soft skills

• First-principles thinker

  questions assumptions, proposes novel solutions.

• Bias for action

  prototypes in hours, not weeks; embraces agile experimentation.

• Storytelling ability

  explains complex models in clear, executive-friendly language.

• Ownership mentality

  treats the prototype as a product, not just a demo.

7. Tech stack youll touch

Python | PyTorch | Hugging Face | TensorRT | LangChain | Neo4j/GraphDB | PostgreSQL | Airflow | MLflow | Weights & Biases | Docker | GitHub Actions | JAX (exploratory)

8. Internship logistics & perks

• Competitive monthly stipend + performance bonus.
• High-end workstation + GPU credits on our private cloud.
• Dedicated mentor and 30-60-90-day learning plan.
• Access to premium research portals and paid conference passes.
• Culture of radical candor, weekly brown-bag tech talks, and hack days.
• Fast-track to full-time

  AI Research Engineer

  upon successful completion.

9. Application process

1. Apply via email:

   Send rsum, brief statement of purpose, and GitHub/portfolio links to

   [HIDDEN TEXT]

   .

2. Online coding assessment:

   algorithmic + ML fundamentals.

3. Technical interview (2 rounds):

   deep dive into projects, math, and research reasoning.

4. Culture-fit discussion:

   with Research Lead & CPO.

5. Offer & onboarding

   target turnaround < 3 weeks.