Location: On-site, Berkeley, California

Experience Level: 0-2 years

Type: Full-time based out of Berkeley office

Compensation: Top-of-market cash compensation with meaningful equity (0.1 to 0.3%)

About SigIQ.ai

At SigIQ, we’re building the AI infrastructure for the next era of learning — starting with PadhAI, India’s #1 ranked AI tutor that beat 1.3M students and even GPT-4o in live standardized testing. Backed by GSV Ventures, The House Fund, Peak XV (Sequoia India), and Duolingo, we’ve raised $10M to make one-on-one, world-class tutoring accessible to every learner.

Achievements in a snapshot:

• Two consumer products with over 300,000+ student users combined.
• Top-5 EdTech seed round in 2024 ($10M) backed by GSV Ventures, Sequoia India, The House Fund, Duolingo as well as amazing angels Christian Storm (CTO, Turnitin), Andy Konwinski (Co-founder, Perplexity), Prof. Trevor Darrell, Prof. Jitendra Malik, Prof. Stuart Russell (BAIR, UC Berkeley) and others.
• Currently, working on ET Live: a real‑time zoom like tutoring experience that delivers instant, personalized guidance. You will directly contribute to building it.

You will work directly with our Founder and CEO, Dr. Karttikeya Mangalam (PhD in AI from UC Berkeley) and co-founder Prof. Kurt Keutzer, Berkeley EECS legend and serial entrepreneur.

Role Overview

We are hiring an AI/ML Engineer to design, prototype, and ship machine learning systems with a strong focus on LLM workflows, real-world evaluation, and deployment readiness. This is not a research position. You will work closely with our founding team, AI researchers, and product engineers to bring powerful AI into real student experiences.

Responsibilities

• Build, scale, and own ML/AI systems.

• Design evaluation pipelines and apply them to iteratively improve the systems we build.

• Collaborate with PMs, designers, and engineers to ship student-facing ML features.

• Drive high-quality, high-speed execution in a startup environment.
  

Must-Have Qualifications

• 0 to 2 years of professional ML engineering experience, ideally in product-facing roles.

• Strong machine learning and software engineering skills.

• Experience with our stack: Python, FastAPI/Django, Postgres.

• Hands-on experience with LLMs including orchestration, context management, evaluation, and fine-tuning.

• Experience working with cloud platforms like AWS, GCP, or Azure.

• Passion to build things and a very strong will to make your time on earth worth it

Nice-to-Have

• Background in early-stage startups or 0 to 1 product development

• Familiarity with AI/ML frameworks like Pytorch, vLLM, Huggingface

• Strong product intuition and ability to scope fast experiments

• Shipped internal tools, open-source demos, or custom evaluation pipelines

• Hustle spirit and battle scares to prove it
  

Perks & Benefits

• Competitive cash plus equity package

• Direct mentorship from top AI researchers and senior engineers

• Your work ships fast and impacts students directly