Experience: 3.00 + years
Salary: Confidential (based on experience)
Shift: (GMT+05:30) Asia/Kolkata (IST)
Opportunity Type: Office ()
Placement Type: Full time Permanent Position
(*Note: This is a requirement for one of Uplers client - Cravv)
What do you need for this opportunity
Must have skills required:
Computer Vision, Deep Learning, Machine Learning, LLMs, Vlm, SAM, Transformers
Cravv is Looking for:
Job Description:
C R A V V
Revolutionizing the kitchen experience
Lead AI Engineer
Location: Onsite, Bangalore | Experience: 3–6 years | Reports to: CTO
Compensation: Best in the industry
A B O U T C R A V V
Cravv is building the future of the kitchen. We're creating a centralized ecosystem of smart devices and appliances that work in tandem to make cooking less stressful and more intuitive. Think of it as the nervous system for your kitchen — where every device talks to every other, and the whole thing just works.
We're a small, fast-moving team that ships real products. No fluff, no theatre. If you're looking for a place where your work directly shapes the product and the company, this is it.
T H E R O L E
We're looking for a Lead AI Engineer who can own our AI stack end-to-end — from research and prototyping to production deployment and optimization. You'll be building the intelligence layer that powers Cravv's voice-first smart kitchen devices. This means working across computer vision, natural language processing, and speech — designing systems that run reliably in real-time on real hardware.
You'll report directly to the CTO and have significant influence on technical direction. This isn't a role where you'll be handed a spec and asked to execute. You'll be expected to figure out what needs to be built and how.
W H A T Y O U L L D O
- Design and build complex, asynchronous, real-world systems that integrate AI models into production infrastructure.
- Work with transformer-based architectures (LLMs, VLMs, SAM, and beyond) across computer vision and NLP pipelines.
- Build and optimize voice pipelines — TTS and STT systems that power Cravv's voice-first devices.
- Deploy and optimize large models on cloud platforms (AWS, GCP) for real-time latency requirements.
- Build and maintain inference pipelines using engines like vLLM, ensuring reliability and performance at scale.
- Write production-grade, scalable code with high standards — clean architecture, proper testing, thorough documentation.
- Leverage AI-assisted development tools like Claude Code to ship faster without compromising quality.
- Make architectural decisions on model selection, training strategies, and system design trade-offs.
- Stay on top of the latest developments in AI — new models, techniques, and tooling — and bring what's relevant into the product.
- Lead a small engineering team — set direction, unblock people, and maintain high technical standards.
- Collaborate with product, hardware, and design teams to translate ambiguous problems into working solutions.
W H A T W E R E L O O K I N G F O R
Technical
- 3–6 years of hands-on experience in ML/DL, with real production deployments (not just Kaggle medals).
- Strong system design skills — you can architect complex asynchronous systems and reason about failure modes, throughput, and latency.
- Deep familiarity with transformer-based architectures: LLMs, VLMs, SAM, and the foundational building blocks (CNNs, RNNs, attention mechanisms).
- Basic understanding of TTS and STT pipelines and current state-of-the-art models in the speech domain.
- Solid experience with PyTorch. You write clean, maintainable model code.
- You write production-grade, scalable code — not notebook prototypes. Proper abstractions, error handling, testing, and documentation are non-negotiable.
- Proficiency in Python. C++ is a strong plus.
- Hands-on experience deploying and optimizing models on AWS or GCP for real-time inference.
- Familiarity with inference engines like vLLM.
- Comfortable using AI-assisted development tools (Claude Code, Cursor, etc.) to accelerate development velocity.
- Actively keeps up with the fast-moving AI landscape — new papers, models, frameworks, and tooling. You know what shipped last month, not just last year.
Nice to Have
- Experience with training and fine-tuning LLMs and VLMs.
- Deeper experience in speech/audio processing beyond basic TTS/STT pipelines.
- Experience with edge deployment and model optimization for on-device inference.
Non-Technical
- Experience leading small engineering teams. You don't need a management title — you need to have actually done it.
- Startup experience. You know what it means to operate with limited resources and high ambiguity.
- Strong ownership mindset — you see problems and fix them without being asked.
- Clear, direct communication. You can hold your own in conversations with product, design, and leadership.
- Goal-oriented. You care about outcomes, not activity.
W H Y C R A V V
- You'll work on AI that ships into physical products people use every day — not another chatbot wrapper.
- Direct access to leadership and real influence on technical direction.
- Compensation that's best in the industry. We don't lowball.
- A team that values substance over optics. No standups-about-standups.
How to apply for this opportunity
- Step 1: Click On Apply! And Register or Login on our portal.
- Step 2: Complete the Screening Form & Upload updated Resume
- Step 3: Increase your chances to get shortlisted & meet the client for the Interview!
About Uplers:
Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement.
(Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well).
So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!
