Niche Expertise
Data & AI Staffing
Data engineers, ML engineers, data scientists and analytics leaders who build production pipelines, not just Jupyter notebooks.
- ML focus
- Production
- LLM specialists
- GenAI
- data to deploy
- Full Stack
What this is
What we do, and what it leaves you with.
The data and AI talent market is noisy — everyone claims ML experience, but few have deployed models to production. Talpro's Data & AI practice screens for engineers who have built and maintained real data pipelines, trained and served ML models at scale, and understand the full MLOps lifecycle from experiment tracking to monitoring.
Why Talpro
- Production ML focus: model serving, A/B testing, monitoring
- Full data stack: Spark, Airflow, dbt, Snowflake, Databricks
- GenAI and LLM specialists (RAG, fine-tuning, prompt engineering)
- Domain-specific data talent for FinTech, Healthcare, E-commerce
Capabilities
The bench, by discipline.
Named skills, not adjectives. Every line is a discipline we have placed in the last twelve months.
Data Engineering
- Apache Spark, Kafka, Flink (streaming)
- Airflow, Dagster, Prefect (orchestration)
- dbt, Snowflake, BigQuery, Redshift (warehousing)
- Data modelling and quality frameworks
Machine Learning & AI
- PyTorch, TensorFlow, scikit-learn
- MLOps: MLflow, Kubeflow, SageMaker, Vertex AI
- NLP, Computer Vision, Time Series
- GenAI: LLM fine-tuning, RAG architectures, LangChain
- Responsible AI and model governance
Analytics & BI
- Product analytics and experimentation
- BI tools: Looker, Tableau, Power BI, Metabase
- Customer data platforms and segmentation
- Revenue and marketing analytics
Roles
Roles we hire.
- Data Engineer
- Senior Data Engineer
- ML Engineer
- Data Scientist
- MLOps Engineer
- Analytics Engineer
- BI Developer
- Head of Data
- GenAI Engineer
- NLP Engineer
- Computer Vision Engineer
Industries
Industries we serve.
- FinTech
- Healthcare
- E-commerce
- SaaS
- AdTech
- Gaming
- Logistics
How it runs
From requirement sign-off to the first day, in order.
Each step has an owner and an exit; nothing moves until the previous step is true.
- 01
Discovery
goals, roles, must‑haves & timelines
- 02
Market search & targeted outreach
- 03
Talpro screening
skills, scenario & culture fit
- 04
Shortlist & interview coordination
- 05
Offer, onboarding & compliance
- 06
Post‑join follow‑up and ramp support
Representative outcome
“We needed ML engineers who could deploy models, not just build them in notebooks. Talpro's assessment caught the difference — every hire was production-ready from day one.”
FAQ
Data & AI Staffing — the questions we get first.
What data and AI roles does Talpro staff?
We place Data Engineers, ML Engineers, Data Scientists, MLOps Engineers, Analytics Engineers, GenAI/LLM Engineers, NLP specialists, and data leadership roles.
How does Talpro assess ML engineering candidates?
We use a production-focused assessment: candidates work through real ML scenarios including feature engineering, model training, deployment pipelines, monitoring, and A/B testing — not just Kaggle competitions.
Can Talpro hire GenAI and LLM specialists?
Yes. We have an active pipeline of engineers with hands-on experience in LLM fine-tuning, RAG architectures, LangChain/LlamaIndex, prompt engineering, and vector databases.
What industries does Talpro's data staffing cover?
We serve FinTech (fraud models, risk scoring), Healthcare (diagnostic AI, clinical NLP), E-commerce (recommendations, search ranking), SaaS (product analytics), and more.
Response time
To a signed requirement
Industries covered
Sector hubs published on this site
Stages in the BOT model
Advise, establish, build, scale, transfer
Founder years in IT staffing
Bhaskar Anand · Talpro India since 2020
Start with a requirement, or start with a conversation.
Shortlist
Send the requirement
A signed requirement gets a first shortlist typically inside 48 hours, with the screening notes attached.
Hire Data & AI TalentBigger question
Building a center, not just a team?
Twelve questions; a readiness band and a recommended engagement model.
Take the GCC Readiness Assessment