Senior TA (AI&ML Hiring)

Job description

**Group Company:** LeadSquared **Designation:** Senior Talent Acquisition Specialist – AI, ML & Data Engineering Hiring **Office Location:** [ Bengaluru] (4 days work from office, 1 day flexible/remote) **Position description:** The Senior TA Specialist – AI, ML & Data Engineering at LeadSquared will own end-to-end recruitment across AI Engineering, Machine Learning, Data Engineering, and Data Science functions — from individual contributors to team leads. This role requires strong technical fluency across the AI/data stack, the ability to independently assess technical talent, and proven experience building AI/data teams from the ground up within a SaaS/product environment. **Primary Responsibilities** - Manage full-cycle recruitment across AI/ML and Data roles, including AI Engineers, ML Engineers, Data Engineers, Data Scientists, MLOps Engineers, Applied/Research Scientists, and AI Product roles - Partner with hiring managers and engineering leaders to define role requirements, sourcing strategy, and hiring timelines for each specialization - Build and execute sourcing strategies for niche AI/data talent using LinkedIn, GitHub, Kaggle, Stack Overflow, AI/data communities and conferences, and referral networks - Screen candidates for technical fit, cultural alignment, and career motivation, factoring in the distinct skill sets of AI/ML vs. data engineering roles - Design and continuously improve technical interview processes in collaboration with engineering stakeholders across AI, ML, and Data Engineering teams - Manage offer negotiations and closing for competitive AI/ML/Data talent - Build and maintain strong talent pipelines across AI, ML, and Data Engineering to support LeadSquared's growing AI initiatives - Track and report hiring metrics (time-to-fill, source effectiveness, offer-to-join ratio) by role category **Additional Responsibilities** - Support employer branding initiatives targeted at AI/ML and Data Engineering talent communities (tech talks, hackathons, university/SaaS ecosystem partnerships) - Advise leadership on market compensation trends and talent availability across AI, ML, and Data Engineering functions - Mentor junior recruiters on technical sourcing and evaluation techniques for data-heavy roles - Contribute to workforce planning for scaling LeadSquared's AI and data teams **Reporting Team** - Reporting Designation: TA Manager / Head of Talent Acquisition - Reporting Department: Human Resources / People & Talent **Educational Qualifications Preferred** - Category: Full-time - Field specialization: Human Resources, Business Administration, or related field (Computer Science/Engineering background is a plus) - Degree: Bachelor's degree (master's preferred but not mandatory) **Required Work Experience** - Industry: SaaS / Technology / Product-based companies (mandatory SaaS background) - Role: Technical Recruiter / Talent Acquisition Specialist - Years of experience: 4–5 years overall in technical recruitment within a SaaS company, including at least 1.5 years specifically building AI/ML/Data Engineering teams (from scratch or scaling existing teams) **Key Performance Indicators** - Time-to-fill for AI/ML and Data Engineering roles - Offer acceptance rate - Quality of hire (retention at 6/12 months) - Diversity of candidate pipeline - Hiring manager satisfaction score - Sourcing channel effectiveness across role categories **Required Competencies** - Strong stakeholder management and consultative hiring approach - Ability to evaluate technical AI/ML and Data Engineering talent independent of engineering support - Negotiation and closing skills for competitive/niche talent - Data-driven decision-making - Adaptability across multiple concurrent hiring lines (AI, ML, Data Engineering) **Required Knowledge** - Strong understanding of AI/ML and Data Engineering concepts, roles, and career paths (e.g., differences between AI Engineer, ML Engineer, Data Engineer, Data Scientist, MLOps Engineer) - Familiarity with relevant tech stacks — Python, TensorFlow, PyTorch, LLMs, NLP, Computer Vision for AI/ML; SQL, Spark, Airflow, Kafka, ETL/ELT pipelines, cloud data platforms (AWS/GCP/Azure) for Data Engineering — enough to evaluate resumes and hold informed conversations with candidates - Understanding of the SaaS business model and how AI/data teams are structured within product companies - Knowledge of current compensation benchmarks and market trends across AI, ML, and Data Engineering talent - Understanding of applicant tracking systems (ATS) and sourcing tools **Required Skills** - Advanced sourcing (Boolean search, GitHub/Kaggle mining, LinkedIn Recruiter) - Technical screening and competency-based interviewing across multiple technical disciplines - Strong written and verbal communication - Pipeline and stakeholder reporting - Employer branding and candidate experience management **Required Abilities** - Physical: Standard office/desk-based work; comfortable working from office 4 days a week - Other: Ability to manage multiple concurrent open roles across different technical specializations; resilience in a competitive hiring market **Work Environment Details:** Fast-paced, target-driven SaaS environment; 4 days work from office, 1 day flexible/remote; close collaboration with engineering, data, and leadership teams