AI Engineering Intern

Round 1: Online Aptitude & Logical Reasoning Test → Round 2: Technical Interview (coding & ML concepts) → Round 3: HR Interview

Amber promotes a flat hierarchy where ideas are judged on merit, not seniority. Employees enjoy flexible working hours, regular knowledge‑sharing sessions, and a strong emphasis on work‑life balance, with occasional hackathons and team outings to foster camaraderie.

Amber’s interview process typically starts with a timed online aptitude test, followed by a technical interview that blends coding challenges with machine‑learning concepts. The final HR round focuses on cultural fit and communication skills. Candidates should be comfortable with Python coding, basic statistics, and be prepared to discuss recent AI projects or coursework.

• Currently pursuing or recently graduated (within the last 12 months) with a B.Tech/M.Tech/B.Sc. in Computer Science, Computer Engineering, Information Technology, or a related technical discipline. • Minimum aggregate of 60% (or CGPA 6.0/10) in the qualifying degree. • No active backlogs at the time of application. • Batch year can be 2023, 2024, or 2025 (flexible for recent graduates). • Strong academic foundation in algorithms, data structures, and basic machine‑learning concepts. • Ability to work on‑site in Pune for the full internship duration.

Amber is a fast‑growing technology startup headquartered in Pune, Maharashtra. Founded in 2018, the company focuses on building AI‑driven solutions for sectors such as healthcare, finance, and e‑commerce. With a team of over 150 engineers, data scientists, and product designers, Amber prides itself on a culture of rapid experimentation, collaborative problem‑solving, and continuous learning. The firm has recently secured Series A funding, which is being channelled into expanding its research labs and launching new AI products that aim to automate decision‑making and improve user experiences. The AI Engineering Intern role is designed for fresh talent eager to dive into real‑world artificial‑intelligence projects. Interns will work side‑by‑side with senior machine‑learning engineers, product managers, and data analysts to design, develop, and deploy models that power Amber’s flagship platforms. This is a full‑time, on‑site internship that offers hands‑on exposure to the end‑to‑end AI development lifecycle—from data ingestion and preprocessing to model training, evaluation, and production monitoring. Key Responsibilities: 1. Assist in collecting, cleaning, and preprocessing large datasets from diverse sources. 2. Develop and fine‑tune machine‑learning models using Python libraries such as scikit‑learn, TensorFlow, or PyTorch. 3. Write modular, well‑documented code and contribute to the company’s shared codebase on Git. 4. Participate in model evaluation, performance benchmarking, and error analysis. 5. Collaborate with product teams to translate business requirements into technical specifications. 6. Deploy prototypes to cloud environments (AWS/GCP) and monitor model drift. 7. Prepare technical reports and visualisations to communicate findings to non‑technical stakeholders. 8. Stay updated with the latest research papers and suggest innovative approaches for ongoing projects. 9. Support the team in building data pipelines and automation scripts. 10. Participate in code reviews and knowledge‑sharing sessions. Tech Stack: Python, Pandas, NumPy, scikit‑learn, TensorFlow/PyTorch, SQL, Git, Docker, AWS/GCP, Jupyter notebooks. Growth Path: Successful interns may be offered a full‑time Junior Machine‑Learning Engineer position, with clear progression to Senior Engineer, Lead AI Engineer, and eventually AI Product Manager roles. Amber encourages continuous upskilling through internal workshops, conference sponsorships, and mentorship programs. Why Join Amber? The internship provides a rare blend of startup agility and structured mentorship. Interns gain exposure to production‑grade AI systems, work on projects that impact real customers, and become part of a supportive community that values curiosity and impact. This experience can serve as a strong launchpad for a career in AI engineering.