Senior TA (AI&ML ) Professional

Job Summary

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.

Responsibilities

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: 45 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

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.