{"id":3176874,"url":"https://alion.io/job/valiance-talent-acquisition-specialist","title":"Talent Acquisition Specialist","company":{"id":3997487,"name":"Valiance","domain":"valiance.io","url":"https://alion.io/company/valiance","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"HR","role_family":"HR","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Noida, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":5500,"max_usd":12000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":11},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Computer Vision","optional":false},{"name":"LinkedIn","optional":false},{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-10-23T17:37:44Z","employer_posted_date":null,"last_verified_at":"2026-10-23T17:37:44Z","board_verified":false,"closed_at":null,"days_open":12,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":12},"description":"About Valiance\nValiance is a deep-tech AI and analytics consulting firm working with enterprises on cutting-edge solutions across Artificial Intelligence, Generative AI, Data Science, Computer Vision, Data Engineering, and Cloud Engineering.\nOur teams solve complex business problems for leading enterprises using modern AI technologies and data platforms. We are looking for a Technical Recruiter who can help us build exceptional engineering and AI teams by identifying, evaluating, and attracting high-quality technical talent.\n\nThe Role\nWe are looking for a recruiter who goes beyond sourcing resumes and matching keywords against job descriptions. Someone who understands technology, can recognize meaningful technical experience, distinguishes genuine expertise from superficial exposure, and exercises sound judgment when evaluating candidates.\nYou should be curious, proactive, analytical, and highly outcome-oriented. You should continuously learn from interview feedback, identify gaps in the recruitment process, and bring ideas to improve hiring quality and speed.\nWe value independent thinking, ownership, and the ability to make good decisions in ambiguous situations. AI tools should help you become more effective and productive, but your judgment, curiosity, and ability to identify talent must remain your own.\n\nKey Responsibilities\n1. Technical Screening & Talent Evaluation\nEvaluate resumes against job requirements by understanding the substance of a candidate's experience, not merely matching keywords or listed skills.\nIdentify relevant projects, assess their complexity, understand the candidate's specific contributions, and evaluate the depth and duration of their hands-on experience.\nDistinguish between candidates who have genuinely built and deployed solutions and those with only academic exposure, superficial familiarity, or limited practical experience.\nAssess candidates for roles across Data Science, Machine Learning, Generative AI, Computer Vision, Data Engineering, and related technical disciplines.\nIdentify relevant transferable skills and non-obvious talent that may not have an exact keyword match with the job description.\nApply sound judgment to shortlist candidates who merit further technical evaluation, while avoiding both false positives and the rejection of promising profiles.\n2. Candidate Fitment & Hiring Judgment\nEvaluate candidates across technical relevance, problem-solving ability, communication, learning agility, motivation, ownership, and role-specific expectations.\nRecognize signals that indicate whether a candidate is suited to the role, the nature of consulting work, client-facing environments, and Valiance's working culture.\nUnderstand the differences between profiles that look similar on paper but vary significantly in capability, experience, and potential.\nAsk thoughtful screening questions to validate experience, uncover gaps, and establish whether a candidate's claims are supported by concrete examples.\nMaintain a high bar for hiring quality without unnecessarily narrowing the talent pool.\n3. Learning from Interview Outcomes\nSystematically analyze feedback from technical interviews, hiring managers, and rejected candidates to understand what worked and what did not.\nIdentify patterns in rejected profiles, including recurring gaps in technical depth, project experience, communication, or role fit.\nTranslate feedback into improved screening criteria, sharper questions, better sourcing strategies, and more accurate shortlisting decisions.\nTrack the quality of shortlisted candidates and continuously refine the recruitment process based on actual outcomes.\nDemonstrate measurable improvement in screening accuracy and hiring effectiveness over time.\n4. Ownership, Agency & Continuous Improvement\nTake end-to-end ownership of assigned hiring mandates, from understanding requirements and sourcing through screening, interview coordination, and offer closure.\nProactively identify bottlenecks, hiring risks, and opportunities to improve candidate quality, turnaround time, and conversion rates.\nBring recommendations and challenge ineffective approaches constructively instead of waiting for instructions.\nCollaborate closely with hiring managers, interviewers, and the broader talent acquisition team to align on role expectations and hiring priorities.\nFollow through on commitments, communicate issues early, and remain accountable for outcomes rather than activity alone.\nShow curiosity, energy, and a genuine hunger to improve personal effectiveness and the overall quality of hiring.\n5. Effective Use of AI & Recruitment Tools\nUse AI tools to improve sourcing, resume analysis, candidate research, interview preparation, and recruitment workflow efficiency.\nApply independent judgment to validate AI-generated assessments, challenge incorrect conclusions, and identify context that automated screening may miss.\nAvoid relying on AI-generated shortlists without independently evaluating candidate experience, project relevance, technical depth, and role fit.\nExperiment with better recruitment workflows and share practical ideas that improve productivity without compromising hiring quality.\nUse AI responsibly, protecting candidate information and complying with company data security policies.\n\nWhat We Are Looking For\n2–4 years of experience in technical recruitment, preferably hiring for Data Science, Machine Learning, Generative AI, Data Engineering, or software engineering roles.\nPrior experience recruiting for an AI company, data consulting firm, deep-tech organization, or technology product company is strongly preferred.\nA working understanding of technical concepts, project lifecycles, and the practical differences between commonly used technologies and skill sets.\nStrong analytical thinking and the ability to interpret resumes beyond keywords, titles, and years of experience.\nEvidence of good candidate judgment and the ability to distinguish high-quality profiles from superficially suitable ones.\nA track record of taking initiative, solving problems independently, and improving recruitment processes.\nStrong communication and stakeholder management skills, with the confidence to engage technical hiring managers and ask clarifying questions.\nComfort working in a fast-paced environment with multiple hiring priorities and evolving requirements.\nFamiliarity with applicant tracking systems, sourcing platforms, LinkedIn Recruiter, and AI-enabled recruitment tools.\n\nWe will place particular emphasis on:\nTalent intuition backed by evidence: The ability to spot promising candidates by understanding what they have actually done, not simply what their resumes claim.\nIndependent thinking: The willingness and ability to make reasoned decisions rather than blindly follow templates, keywords, or AI recommendations.\nHigh agency: Identifying what needs to be done, taking initiative, and driving it to completion without constant supervision.\nLearning agility: Converting feedback and mistakes into better screening decisions and stronger recruitment outcomes.\nOutcome orientation: Caring about the quality of candidates hired, not just the number of resumes sourced or calls completed.\nCollaborative mindset: Working as a partner to hiring managers and colleagues, sharing insights, and actively seeking feedback.\nContinuous improvement: Bringing ideas, testing new approaches, and raising the bar on recruitment effectiveness.\n\nHow Success Will Be Measured\nQuality and relevance of shortlisted candidates, measured through technical interview progression and hiring manager feedback.\nScreening accuracy, including the ability to identify suitable candidates and reduce avoidable mismatches.\nImprovement in interview-to-shortlist and interview-to-offer conversion rates, with appropriate role-level context.\nHiring turnaround time and ability to maintain healthy candidate pipelines for priority positions.\nCandidate engagement, interview coordination, and offer conversion.\nEvidence of learning from feedback and sustained improvement in recruitment decisions.\nProactive recommendations and measurable improvements to recruitment workflows and productivity.\n\nWhy Join Valiance\nWork closely with experienced AI, Data Science, and Data Engineering professionals.\nDevelop a deeper understanding of emerging technologies and the talent shaping enterprise AI.\nTake ownership of hiring outcomes in a growing deep-tech organization.\nHave the opportunity to influence and improve how a technology company identifies and 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