Machine Learning Engineers
Vetted Tier-1 ML engineers embedded into your team. Predictive models, recommendation systems, NLP, LLM fine-tuning, MLOps — sprint-delivered, Engagement Manager audited.
Two-week risk-free trial. No lock-in.
< 48h
Time to match
Top 1%
Engineer tier
100%
IP ownership
2 weeks
Risk-free trial
What They Build
Churn prediction, demand forecasting, fraud detection, credit scoring — trained, validated, and deployed to production.
Collaborative filtering, content-based, and hybrid recommender engines for e-commerce, SaaS, and media platforms.
Sentiment analysis, entity extraction, text classification, summarisation — from BERT fine-tuning to custom transformer models.
Fine-tune foundation models on your data. Build RAG pipelines that retrieve and reason over your knowledge base accurately.
Sales forecasting, predictive maintenance, anomaly detection in logs, metrics, or IoT sensor data.
Model versioning, automated retraining, drift monitoring, A/B testing infrastructure — making ML reliable in production.
Who It's For
You have a product that needs ML capabilities but no in-house expertise. Get a vetted ML engineer embedded in 48 hours — not 3 months of hiring cycles.
Your data scientists have models but struggle to productionise them. An ML engineer bridges the gap between experiment and production.
You know what ML needs to power your product but can't hire fast enough. Sprint-gated delivery, one point of contact, no vendor chaos.
How It Works
Fill a 5-minute intake form describing your ML use case, data situation, existing stack, and goals. A Delivery Lead contacts you within 24 hours.
We surface 2–3 hand-picked ML engineers with proven experience in your domain and tech stack. You review profiles, join intro calls, and choose your fit.
Your engineer works in focused sprints. An Engagement Manager audits every milestone. You get working, production-ready ML systems — not notebooks, not experiments.
Tell us your use case. Matched in 48 hours. 2-week risk-free trial.
What's Included
Every ML engineer passes a rigorous 5-stage vetting — statistics & theory, ML system design, coding, model evaluation, and live delivery simulation.
A senior Kovil AI lead audits every milestone before it reaches you. Model accuracy, data leakage, production readiness — all verified.
Work happens in structured weekly sprints with clear deliverables. Not open-ended hours billed to a Jira ticket.
Specialists across supervised learning, deep learning, NLP, recommendation systems, time series, tabular ML, and LLM fine-tuning.
Your engineer owns the full stack — data ingestion, feature engineering, model training, versioning, CI/CD for ML, and production monitoring.
We don't just build models — we deploy them. FastAPI, BentoML, SageMaker, Vertex AI, or your own infra. Monitored and maintained.
What to Expect
Fill a 5-minute intake form. A Delivery Lead calls you within 24 hours to scope requirements, data situation, and preferred stack.
We surface 2–3 ML engineers matched to your domain. You review profiles, join intro calls, and choose your fit.
You and your engineer agree a sprint plan — model targets, accuracy benchmarks, timelines, and success criteria before any work begins.
Your engineer works in focused sprints. Your Engagement Manager audits every output. You review at each milestone checkpoint.
Add engineers, extend sprints, or wind down — no lock-in. You stay because it's working, not because you're contracted.
Why Kovil AI
| Kovil AI | In-House Hire | Big Agency | Freelancer | |
|---|---|---|---|---|
| Time to start | 24–48 hours | 2–3 months | 2–4 weeks | 1–2 weeks |
| ML specialisation | Deep domain | Varies | Varies | Varies |
| Managed delivery | ✓ Always | ✗ | Partial | ✗ |
| Risk-free trial | ✓ 2 weeks | ✗ | ✗ | Rarely |
| MLOps included | ✓ Always | Separate hire | Extra cost | Rarely |
| IP ownership | 100% yours | 100% yours | Often shared | Varies |
FAQ
Explore More
Tell us your use case. Matched in 48 hours. 2-week risk-free trial.