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Machine Learning & Data Science Engineer Job Opening In Gurugram – Now Hiring whitetable.ai


Job description

<p><b style="background-color: inherit;">What You'll Work On :</b><br/><br/>- Develop state-of-the-art time series models for anomaly detection and forecasting in observability data.<br/><br/>- Design a root cause analysis system using LLMs, causal analysis, machine learning and anomaly detection algorithms.<br/><br/>- Develop Large Language Models for time series analysis<br/><br/>- Create highly scalable ML pipelines for real-time monitoring and alerting.<br/><br/>- Build and maintain ML Ops workflows for model deployment, evaluation, monitoring, and updates.<br/><br/>- Build frameworks to evaluate AI agents.<br/><br/>- Handle large datasets using Python and its ML ecosystem (e.g., NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, Statsmodels).<br/><br/>- Use Bayesian methods, Granger causality, counterfactual analysis, and other techniques to derive meaningful system insights.<br/><br/>- Collaborate with other teams to deploy ML-driven observability solutions in production.<br/><br/></p><p><b>What We're Looking For :</b></p><p><b><br/></b></p><p>- 5+ years of hands-on experience in Machine Learning, Time Series Analysis, and Causal Analytics.</p><p><br/></p><p>- Bachelors degree in Computer Science, Mathematics or Statistics.

Masters or PhD is a plus</p><p><br/></p><p>- Strong proficiency in Python and libraries like Scikit-Learn, TensorFlow, PyTorch, Statsmodels, Prophet, or similar.</p><p><br/></p><p>- Deep understanding of time-series modeling, forecasting, and anomaly detection techniques.</p><p><br/></p><p>- Expertise in causal inference, Bayesian statistics, and causal graph modeling.</p><p><br/></p><p>- Experience in ML Ops, model evaluation, and deployment in production environments.</p><p><br/></p><p>- Working knowledge of databases and data processing frameworks (SQL, Spark, Dask, etc.).</p><p><br/></p><p>- Experience in observability, monitoring, or AI-driven system diagnostics is a big plus.</p><p><br/></p><p>- Background in AI Agent evaluation and optimization is a plus.</p><p><br/></p><p>- Working with LLMs, fine-tuning LLMs, LLM Ops, LLM Agents is a big plus</p><p><br/></p><p><b>Our Values :</b></p><p><br/></p><p>- Loyalty & Long-term Commitment - We invest in people who invest in us.</p><p><br/></p><p>- Opinionated yet Open-Minded - We value strong perspectives but encourage constructive discussions.</p><p><br/></p><p>- Passion - We seek individuals who are passionate about their craft.</p><p><br/></p><p>- Humility & Integrity - Honest, transparent, and accountable team members are key.</p><p><br/></p><p>- Adaptability & Self-Sufficiency - Ability to thrive in a fast-paced and evolving environment.</p><p><br/></p><p>- Build Fast and Break Fast - We believe in rapid iteration and learning from failures.</p><br/><b>What You'll Work On:</b><br/><br/>You will be instrumental in building the next-generation Observability platform for automated Root Cause Analysis using LLMs, Machine Learning algorithms.

You will be innovating on building LLMs for time series analysis.

You'll have the opportunity to work with an experienced team, gain deep insights into how startups are built, and be at the forefront of disruptive innovation in Observability.<br/><br/><b>Comp</b> - upto 2Cr+<p></p> (ref:hirist.tech)

Required Skill Profession

Mathematical Science Occupations


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What Is the Average Salary Range for Machine Learning & Data Science Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Gurugram. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Machine Learning & Data Science Engineer typically include Mathematical Science Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Before the Interview:

Research: Learn about the whitetable.ai's mission, values, products, and the specific job requirements and get further information about

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Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

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During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

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Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Final Thought:

To prepare for your Machine Learning & Data Science Engineer interview at whitetable.ai, research the company, understand the job requirements, and practice common interview questions.

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