AI/ML Engineer

Location: Delhi–Gurugram, India | Experience: Mid Level (3–6 years)

About the Company

TheHireHub is an AI-powered talent acquisition platform helping companies find, evaluate, and hire the right talent faster and more efficiently. Founded in 2024, the company is building technology that can reshape how organizations discover and assess exceptional people. Our mission is to revolutionize hiring through AI-powered talent acquisition, with a vision of becoming the leading platform for transforming how companies find and hire talent. The team values innovation, excellence, trust, transparency, and customer-centricity. We are committed to a diverse and inclusive workplace, and our platform promotes fair and unbiased hiring practices. Employees join a fast-paced growth environment where technical excellence, an innovation mindset, customer focus, and collaboration are valued. The role offers an opportunity to influence an important industry while contributing to a product designed to improve hiring speed, quality, and efficiency for employers and candidates.

About the Role

As an AI/ML Engineer, you will own the systems that turn recruitment data and product requirements into reliable, useful intelligence. You will work across machine learning development, experimentation, deployment, and measurement, partnering with engineering and product teams to move models from ideas into customer impact. Your work will improve how talent is discovered, evaluated, and matched while maintaining strong standards for fairness, transparency, and operational reliability. Success means delivering models that perform in production, integrate cleanly with platform services, and create measurable gains in hiring efficiency. This is a hands-on role for an engineer who can balance research-driven problem solving with disciplined software delivery in a fast-moving product environment.

Key Responsibilities

• Own the design, training, evaluation, and improvement of machine learning models that support talent discovery, matching, ranking, and assessment outcomes.
• Build production-grade data and inference pipelines through reproducible workflows, reliable APIs, and monitoring that improve model availability, quality, and operational decision-making.
• Translate product and customer problems into measurable ML objectives, selecting appropriate experiments and evaluation metrics to demonstrate business impact.
• Partner with product, backend, and data stakeholders to integrate models into platform experiences while ensuring maintainability, scalability, and clear ownership across services.
• Establish model monitoring, validation, and feedback loops that identify drift, bias, performance degradation, and opportunities for continuous improvement.
• Document assumptions, experiments, decisions, and results so the team can scale knowledge, review trade-offs, and build on prior work efficiently.
• Contribute to engineering standards, code reviews, testing, and technical decisions that strengthen the reliability of the company’s AI product.

Essential Skills & Technologies

• Strong Python engineering skills with practical experience using machine learning libraries such as scikit-learn, PyTorch, or TensorFlow to build and evaluate production-oriented models.
• Experience with supervised learning, ranking, recommendation, natural language processing, or information retrieval, including sound feature engineering and model evaluation practices.
• Working knowledge of SQL, data preparation, experimentation, and pipeline development across structured and unstructured data sources.
• Experience deploying ML models through APIs, containers, cloud services, or similar production systems with attention to latency, scalability, and observability.
• Ability to communicate model behavior, trade-offs, risks, and business results clearly to technical and non-technical stakeholders.

Additional Plus

• Experience with large language models, embeddings, vector databases, prompt evaluation, or retrieval-augmented generation for talent or enterprise workflows.
• Familiarity with MLOps tools, model registries, feature stores, orchestration platforms, and automated testing for machine learning systems.
• Exposure to responsible AI, fairness measurement, explainability, privacy, or bias mitigation in high-impact decision-support products.

What You'll Bring

• You bring hands-on experience taking machine learning work from problem definition and data exploration through production deployment, measurement, and iteration. You understand that a model creates value only when it works reliably inside a product.
• You combine strong software engineering discipline with practical ML judgment. You can choose appropriate methods, challenge weak assumptions, write maintainable code, and make trade-offs between accuracy, speed, cost, and operational complexity.
• You are comfortable working with ambiguity and converting customer or business needs into testable hypotheses, useful metrics, and delivery plans. You use evidence to decide what to improve and communicate conclusions with clarity.
• You care about the consequences of automated decisions. You look for bias, data quality issues, and failure modes, and you help create systems that are transparent, inclusive, dependable, and aligned with customer trust.
• You work collaboratively across engineering, product, and data disciplines. You share context, invite feedback, document decisions, and take ownership of outcomes rather than limiting yourself to isolated technical tasks.

Why Join Us

• Work on an AI-powered product addressing a meaningful, large-scale challenge: helping companies discover, evaluate, and hire talent more effectively. Your engineering decisions will directly influence product quality and customer outcomes.
• Join a fast-paced growth environment where innovation is expected, technical excellence is respected, and ideas can move quickly from experiment to product. You will have visible ownership as the platform evolves.
• Help shape responsible hiring technology built around trust, transparency, customer-centricity, and fairer practices. The work combines deep technical challenges with measurable impact on an important industry.
• Collaborate with a team that values diverse perspectives, strong communication, and practical problem solving. You will contribute to a mission-driven product while developing breadth across AI, software, and talent technology.

What We Offer

• Competitive compensation and the opportunity to work on a high-impact AI product transforming talent acquisition for modern organizations.
• A hybrid working environment across the Delhi–Gurugram region, supporting collaboration while enabling focused individual work.
• A fast-paced, inclusive team culture grounded in innovation, excellence, trust, transparency, and customer-centricity.