Senior Machine Learning Engineer
HackerRank
Hybrid in Bangalore, IndiahybridPosted 2 months ago
Skill Required
EngineeringMachine Learning EngineerMachine LearningObservabilityPythonNLPGenerative AI
Key highlights
- 4+ years of production ML systems experience required.
- Work on autonomous AI interviewer (Chakra) and fraud‑detection (Integrity) systems.
- Direct access to leadership with fast feedback loops.
- Inclusive, equal‑opportunity employment policy.
- Opportunity to tackle unsolved problems in the agentic era.
- Proficiency in Python and production data pipelines required.
Role overview
Hiring is one of the most consequential decisions a company makes, and over 3,000 enterprises rely on HackerRank to get it right. In this role you will reinvent hiring for the agentic era, building production‑grade ML systems that are the core product—spanning an autonomous AI interviewer (Chakra), fraud‑detection (Integrity), and new technical‑skill evaluation (Evaluation) – and owning the full ML lifecycle from problem framing to deployment and iteration.
Responsibilities
- Design and ship production ML systems across Chakra, integrity, and evaluation domains.
- Own the full ML lifecycle: problem framing, data strategy, experimentation, deployment, and iteration.
- Build evaluation infrastructure and benchmarking pipelines that reliably measure model quality before and after deployment.
- Define the architecture and production bar for different signal categories from scratch.
- Mentor and support junior ML engineers, helping shape their technical thinking and raise the quality bar across the team.
- Establish ML best practices for the team: monitoring, model feedback loops, and quality standards.
Requirements
- 4+ years building and shipping ML systems that run in production at scale.
- Systems thinking comes naturally; model accuracy, data pipelines, serving infrastructure, and customer outcomes are considered a single problem.
- Evaluation methodology matters as much as model performance; a metric measured wrong is worse than no metric.
- Proficient in Python, with practical experience building data pipelines and deploying models to production.
Nice to have
- Experience with multimodal systems: vision, NLP, audio, or behavioral signal pipelines.
- LLM experience: fine‑tuning, RLHF, or multi‑turn agentic systems.
- Background in adversarial ML, fraud detection, or anomaly detection.
- Publications or open‑source contributions in detection, robustness, or evaluation methodology.
Benefits
- Direct access to leadership and fast feedback loops.
- Opportunity to work on genuinely unsolved problems in the agentic era.
- Inclusive, equal‑employment‑opportunity workplace.
Additional details
- HackerRank helps companies like NVIDIA, Amazon, and Microsoft hire and upskill the next generation of developers based on skills, not pedigree.
- The platform is trusted by over 2,500 innovative companies to build strong engineering teams.
- People at HackerRank care deeply about impact, sweat the small details, move with urgency, and hold high standards.
- Open problems include: Chakra (autonomous AI interviewer), Integrity (fraud and suspicious‑behavior detection), and Evaluation (measuring technical skill in a world where AI writes code).
- Focus will shift across these problems depending on where the highest‑leverage work is at any given time.
- You will thrive here if messy, undefined problems interest you more than optimizing within clean ones, ambiguity energizes you, and you enjoy defining new systems rather than maintaining existing ones.
- Company website and social links: HackerRank.com, LinkedIn, X, Blog, Instagram, Life@HackerRank.
- HackerRank is an equal employment opportunity and affirmative action employer; no discrimination based on protected characteristics.
- All applicant information will be kept confidential according to EEO guidelines.
- Notice: Recruiters use @hackerrank.com email addresses; the company never asks for payment or credit‑check information to apply, interview, or work.