AI research engineer Intern Stratsyn AI Technology Service

0.0 years

0 Lacs

Chennai, Tamil Nadu, India

Remote

Job Title: AI Research Engineer Intern (Fresher) Reporting to: Lead Research & Innovation Lab Location: remote/ Hybrid (Chennai, India) Engagement: 6-month, full-time paid internship with pre-placement-offer track 1. Why this role exists Stratsyn AI Technology Services is turbo-charging Stratsyns cloud-native Enterprise Intelligence & Management Suite a modular SaaS ecosystem that fuses advanced AI, low-code automation, multimodal search, and next-generation Virtual workforce agents. The platform unifies strategic planning, document intelligence, workflow orchestration, and real-time analytics, empowering C-suite leaders to simulate scenarios, orchestrate execution, and convert insight into action with unmatched speed and scalability. 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) % FocusKey Responsibility 30 %Rapid Prototyping & Experimentation implement state-of-the-art papers (LLMs, graph learning, causal inference, agents), design ablation studies, benchmark against baselines, and iterate fast. 25 %Data Engineering for Research build reproducible datasets, craft synthetic data when needed, automate ETL pipelines, and enforce experiment tracking (MLflow / Weights & Biases). 20 %Model Evaluation & Explainability create evaluation harnesses (BLEU, ROUGE, MAPE, custom KPIs), visualize error landscapes, and generate executive-ready insights. 15 %Collaboration & Documentation author tech memos, well-annotated notebooks, and contribute to internal knowledge bases; present findings in weekly research stand-ups. 10 %Innovation Scouting scan arXiv, ACL, NeurIPS, ICML, and startup ecosystems; summarize high-impact research and propose areas for IP creation within the Suite. 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 Apply via email: Send rsum, brief statement of purpose, and GitHub/portfolio links to [HIDDEN TEXT] . Online coding assessment: algorithmic + ML fundamentals. Technical interview (2 rounds): deep dive into projects, math, and research reasoning. Culture-fit discussion: with Research Lead & CPO. Offer & onboarding target turnaround < 3 weeks. Show more Show less

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