● 270+ Global Clients · 97% NPS

Hire Machine Learning Engineers in India | ML Recruitment

Machine learning hiring is littered with candidates who have impressive Kaggle profiles but have never deployed a model that serves real users at scale.

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270+

Global Clients

97%

NPS Score

95%

Offer Acceptance

30d

Avg. Time-to-Hire

Start Your Search Brief

Business email required. We respond within 4 hours.

Client Stories

What Our Clients Say

“

Talhive is a wonderful agency that handled the hiring of our junior and senior-level engineers flawlessly. They were responsive, respectful, and diligent. They helped us find the perfect candidates in a very brief timeframe.

Samanyou Garg

CEO, Writesonic

“

Talhive has a very professional team of recruiters who have been a pleasure to work with. They quickly understood our requirements and delivered high-quality candidate profiles in very short time. Thanks to them, we could fill a key position within 4 weeks.

Nikhil Jain

Head of Product, ketteQ

Our Services

What We Deliver

🤖

AI & ML Engineers

Pre-screened on production AI experience.

📊

Data Scientists & Engineers

Verified on real-world pipeline impact.

⚙️

Full-Stack & Backend

Screened on architecture and scale.

🔒

Security & DevOps

Hands-on capability verified.

The Challenge

Hiring the Right Talent Isn't Easy

Market Clamor

Standing out amongst other recruiters is a challenge. With hundreds of agencies pitching the same tired database, your roles become invisible to the talent that matters.

Talent Juggler

Quality candidates juggle multiple job offers simultaneously. Without a compelling pitch and a fast process, they accept a competitor's offer before you've finished scheduling the second interview.

Time Management

Filtering applications to find quality candidates is time-consuming. The average hiring manager spends 13+ hours per week on recruitment admin alone — time stolen from work that actually moves the business.

Why It Matters

The Talent Gap Is a Strategic Risk

70%

of the global workforce is passive — they are not on job boards and will never see your posting.

92%

of job loyalty hinges on an excellent employer brand. Poor positioning loses candidates before the first call.

75%

of hiring costs are spent recovering from bad hires. One wrong placement costs 3–6× the annual salary.

58%

of candidates decline offers due to poor hiring experiences. Your process is your product.

Our Approach

Talhive: Hiring Streamlined

Talhive evaluates ML candidates on production systems experience — serving infrastructure, A/B testing frameworks, feature stores, and retraining pipelines — not just model accuracy on benchmarks. We shortlist engineers who have shipped ML to production at scale.

The Pillars of Talhive Partnership

Specialised Recruitment Desks

Vertical-specialist teams — not generalist recruiters juggling 20 functions at once.

Vast Curated Talent Pool

20,000+ pre-vetted professionals across tech, product, design, sales, data, AI, and finance.

Streamlined Process

Our 8-step methodology ensures swift hires without sacrificing quality. Average: 30 days.

1:5 Hiring Ratio

Maximum 5 candidates per role. Every profile is shortlisted, not just sourced.

Detailed Candidate Synopsis

Full synopsis with background, motivations, culture fit, and technical evaluation.

CDQ Methodology

Career Discovery Questionnaire explores trajectory, aspirations, and skills beyond the CV.

12-Month Guarantee

If the placed candidate leaves within 12 months, we re-run the search at no additional fee.

Our 8-Step Process

Initiate Agreement

Formalise the search mandate and raise the retainer invoice, securing exclusive focus.

Stakeholder Discovery

Deep-dive into the role — intricacies, team dynamics, culture, compensation, success metrics.

Search Manifesto

Detailed search brief documenting everything discussed — our blueprint for sourcing.

Ideal Candidate Profile

Precise person specification for targeted headhunting, not a generic job description.

Candidate Discovery

CDQ process uncovers motivations, aspirations, and interests far beyond the CV.

Synopsis & Evaluation

Shortlisted candidates receive detailed technical evaluations and comprehensive synopses.

Interview Coordination

We manage all interview stages, candidate experience, and extend the offer with full negotiation support.

Close & Guarantee

Post-offer engagement, onboarding support, and project sign-off with our 12-month guarantee.

From the Founders

"I treat every hire as a revenue multiplier, not a headcount filler."

Som Nautiyal

CEO · Strategic Talent Architect

12+ years · 25+ funded startups scaled · B2B GTM hiring advisor

"Great delivery is not speed alone — it's predictable performance under pressure."

Pratik Mokashi

COO · Zero-to-One Team Builder

Scaled delivery from 0 to 120+ tech specialists · SLA-backed metrics

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FAQ

Frequently Asked Questions

What is a machine learning engineer?+

A machine learning engineer bridges data science and software engineering — they build and deploy ML models into production systems. Unlike data scientists who focus on model development, ML engineers focus on model serving, monitoring, retraining pipelines, and scalable ML infrastructure.

What skills should a machine learning engineer have?+

Key skills include: Python (NumPy, pandas, scikit-learn), deep learning frameworks (TensorFlow, PyTorch), feature engineering and model evaluation, MLOps tools (MLflow, Kubeflow, SageMaker), cloud platforms (AWS, GCP), and experience with data pipelines (Spark, Airflow).

What is the salary for a machine learning engineer in India?+

ML engineers in India earn ₹18–45 LPA at mid-level, ₹45–90 LPA for senior/lead roles. Bangalore and Hyderabad are the primary markets. ML roles command a significant premium over general software engineering due to talent scarcity.

How hard is it to hire ML engineers in India?+

ML engineering is one of the hardest technical roles to hire for in India. The talent pool is small relative to demand, and many candidates with ML on their CV lack production experience. Specialist recruitment with genuine technical screening is essential.

Does Talhive recruit for NLP and computer vision specifically?+

Yes. We have placed NLP engineers across text classification, entity extraction, and LLM fine-tuning projects, and computer vision engineers across object detection, segmentation, and video analytics. We can target specific ML subfields based on your product area.