Ai Ml Engineer

V2 Solutions; Hyderabad; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

V2 Solutions is seeking an experienced Senior Data Scientist to translate business problems into analytical solutions and develop end-to-end ML models. The role involves building and deploying models across classification, regression, clustering, and time-series tasks, with emphasis on scalable data pipelines and production-ready deliverables.

You will work with Python/R, SQL, and ML frameworks, and collaborate with data engineers and stakeholders to deliver impactful insights via dashboards and

Qualifications

• 4–6+ years in data science, ML, or applied statistics.
• Strong Python/R programming and SQL proficiency.
• Experience with ML models: classification, regression, clustering, time-series.
• Solid knowledge of statistics, hypothesis testing, and experimental design.
• Experience deploying models to production; familiarity with APIs and containerization.

Responsibilities

• Collaborate with stakeholders to translate problems into analytical solutions.
• Design, develop, and deploy predictive models (classification, regression, time-series).
• Conduct EDA, data cleaning, preprocessing, and feature engineering.
• Validate insights with statistical tests and experiments.
• Build scalable data pipelines with data engineers.
• Deploy ML models using APIs, containers, and MLOps practices.
• Utilize cloud platforms (Azure, AWS, GCP) for training and deployment.
• Create interactive dashboards with Power BI/Tableau for stakeholders.
• Communicate findings through reports and data storytelling.
• Stay updated on ML/AI advances to drive innovation.

Skills

Python

R

SQL

Statistics

Data analysis

Communication

Problem-solving

Pandas

NumPy

scikit-learn

XGBoost

LightGBM

TensorFlow

PyTorch

FastAPI

Docker

Kubernetes

Azure ML

AWS SageMaker

GCP Vertex AI

Spark

Databricks

MLflow

Education

Bachelors/ Masters in Data Science, CS, Statistics, Math, Engineering

Tools

Python

R

SQL

scikit-learn

XGBoost

LightGBM

TensorFlow

PyTorch

FastAPI

Docker

Kubernetes

Azure ML

SageMaker

Vertex AI

Spark

PySpark

Databricks

MLflow

Job description

Responsibilities

• Collaborate with business stakeholders to understand problem statements and translate them into analytical solutions.
• Design, develop, and deploy predictive models including classification, regression, clustering, and time-series forecasting models.
• Perform exploratory data analysis (EDA), data cleaning, preprocessing, and feature engineering on structured and unstructured datasets.
• Apply statistical techniques including hypothesis testing and experimental design to validate insights and model performance.
• Work closely with data engineers to build and maintain scalable data pipelines and ensure efficient data processing.
• Deploy machine learning models into production environments using APIs and containerization technologies.
• Implement MLOps best practices including model versioning, monitoring, CI/CD integration, and model registries.
• Utilize cloud platforms such as Azure, AWS, or GCP for model training, deployment, and scaling.
• Develop interactive dashboards and visualizations using tools such as Power BI, Tableau, Matplotlib Communicate findings and insights to technical and non-technical stakeholders through reports, presentations, and data storytelling.
• Stay updated with the latest advancements in machine learning, AI, and data science methodologies to drive innovation.

Requirements

• Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 4–6+ years of relevant experience in data science, machine learning, or applied statistics.
• Strong programming proficiency in Python (pandas, NumPy, scikit-learn, statsmodels) and/or R.
• Experience building and validating predictive models (classification, regression, clustering, time-series).
• Strong understanding of statistics, hypothesis testing, and experimental design.
• Proficiency in SQL and experience working with structured and unstructured datasets.
• Hands-on experience with machine learning frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch.
• Experience deploying ML models into production using FastAPI or similar frameworks.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience working with cloud platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI.
• Experience with Spark (PySpark), Databricks, or large-scale data processing frameworks.
• Knowledge of MLOps tools such as MLflow, model registries, and CI/CD pipelines.
• Experience working with SQL/NoSQL databases, Data Lakes, and Blob Storage.
• Strong analytical, problem-solving, and communication skills.
• Ability to work in a fast-paced and dynamic environment.

Nice to Have Skills

• Experience working on AI/LLM-enabled analytics solutions.
• Exposure Generative AI or advanced AI frameworks.
• Experience in building data products or end-to-end ML platforms( pandas,Keras, Tensorflow ).
• Relevant certifications in Data Science, Cloud, or Machine Learning technologies.

Preferred Qualifications

• BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Master’s Degree / MBA from a reputed institute