What are the responsibilities and job description for the Machine Learning Engineer I position at SigIQ.ai?
Location: On-site in Berkeley, California (limited work from home allowed)
Experience Level: 0 to 2 years
Type: Full-time
Compensation:
- Top-of-market cash compensation
- Meaningful equity (0.1 to 0.3%)
- Health insurance & Vision benefits
- Managed 401(k)
- Unlimited paid PTO
- Meals at office 6d/wk,
Overview:
At SigIQ, we’re building the one-on-one AI tutors for the next era of educational learning. Currently, we are hand down building EverTutor Live -- A zoom-like experience with a screen shared whiteboard where an AI tutor (EverTutor) teaches the students math 1:1, in a personalized, interactive manner. This is pioneering a whole new format of learning -- in the same wavelength as prior methods such as videos (that enabled MOOCs), PDFs (that enabled online learning) and printed/written books (like the prior 5000 years before 1990s).
In the past two years, we have launched two prior products as well -- PadhAI, which is #1 ranked UPSC AI tutor that beat 1.3M students and even GPT-4o in live standardized testing. As well as EverTutor, an AI tutor for personalized 1:1 exam prep for the GRE exam.
Our Rocketship in a snapshot:
- Two successful consumer products with over 250,000 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-Haves:
- 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-Haves:
- 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 top of the line equity package
- Direct mentorship and chance to work alongside and learn from top AI researchers & Senior engineers
- Your work ships fast and impacts students directly