Machine learning Engineer

Company Name: VARITE India Private Limited

About The Client:

An Indian multinational information technology (IT) consulting company headquartered in Noida, The company has offices in 52 countries and over 225,944 employees. The Client is a global IT services and consulting company that offers a wide range of services and products across various industries like IT Infrastructure Services, Cybersecurity Services, Cloud Services, Big Data and Analytics, Internet of Things (IoT) Solutions, Semiconductor Services and Enterprise Software Products.

Essential Job Functions:

Data Preparation & Analysis:

• Gather, clean, and preprocess structured, semi-structured, and unstructured data from various sources.
• Conduct exploratory data analysis (EDA) to identify trends, patterns, and outliers.
• Apply data wrangling techniques using Pandas, NumPy, and SQL to transform raw data into usable formats.
• Use statistical analysis to drive data-driven decision-making.

Machine Learning Model Development:

• Build, train, and fine-tune machine learning models using Scikit-learn, TensorFlow, Keras, or PyTorch.
• Develop predictive models, classification algorithms, clustering models, and recommendation systems.
• Conduct hyperparameter optimization using techniques like grid search or random search.

Model Evaluation & Optimization:

• Evaluate model performance using metrics such as Accuracy, Precision, Recall, F1-Score, AUC-ROC, Confusion Matrix, and Cross-validation.
• Improve model performance through techniques such as feature engineering, data augmentation, and regularization.
• Deploy models into production environments, and monitor performance for continual improvement.

Data Visualization & Reporting:

• Develop dashboards and reports using Tableau, Power BI, Matplotlib, Seaborn, or Plotly.
• Present findings through clear visualizations and actionable insights to non-technical stakeholders.
• Write detailed reports on data analysis and machine learning results, ensuring transparency and reproducibility.

Collaboration & Stakeholder Communication:

• Work closely with cross-functional teams (e.g., engineering, product, business) to define data-driven solutions.
• Communicate technical concepts clearly to non-technical stakeholders and provide insights that influence product and business strategy.

Data Pipeline & Automation:

• Design and implement scalable data pipelines for model training and deployment using Airflow, Apache Kafka, or Celery.
• Automate data collection, preprocessing, and feature extraction tasks.

Research & Continuous Learning:

• Stay up-to-date with the latest trends in machine learning, deep learning, and data science methodologies.
• Explore new tools, techniques, and frameworks to improve model accuracy and efficiency.

Qualifications

Required Skills

• Programming Languages: Strong proficiency in Python, with experience in SQL.
• Machine Learning: Hands-on experience with Scikit-learn, TensorFlow, Keras, PyTorch, or similar ML libraries.
• Data Analysis: Strong skills in Pandas, NumPy, and Matplotlib for data manipulation and analysis.
• Statistical Analysis: Experience applying statistical methods to data, including hypothesis testing and regression analysis.
• Cloud Platforms: Familiarity with AWS, Azure, or Google Cloud for deploying models and using cloud-native data services (e.g., AWS Sagemaker, Azure ML).
• Data Visualization: Experience using Tableau, Power BI, Matplotlib, Seaborn, or Plotly for creating visualizations.
• SQL & Databases: Proficiency in SQL for querying relational databases and working with NoSQL databases (e.g., MongoDB, BigQuery).
• Version Control: Experience using Git for version control.

Desirable Skills:

• Big Data Technologies: Familiarity with tools like Apache Hadoop, Spark, Dask, or Google BigQuery for processing large datasets.
• Deep Learning: Experience with deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
• NLP & Computer Vision: Experience with natural language processing (NLP) using spaCy, NLTK, or transformers, and computer vision using OpenCV or TensorFlow.
• MLOps: Familiarity with MLOps tools like Kubeflow, MLflow, or DVC for managing model workflows.
• Data Engineering: Experience with ETL tools like Apache Airflow, Talend, AWS Glue, or Google Dataflow for data pipeline automation.

Tools & Technologies:

• Machine Learning: Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost.
• Data Analysis: Pandas, NumPy, Matplotlib, Seaborn, Plotly.
• Cloud Platforms: AWS, Google Cloud, Azure.
• Databases: MySQL, PostgreSQL, MongoDB, BigQuery, Snowflake.
• Data Visualization: Tableau, Power BI, Matplotlib, Seaborn, Plotly.
• Version Control: Git.

How to Apply: Interested candidates are encouraged to respond/submit their updated resumes, and for additional job opportunities, please visit Jobs In India – VARITE.

Unlock Rewards: Refer Candidates and Earn.

If you're not available or interested in this opportunity, please pass this along to anyone in your network who might be a good fit and interested in our open positions. VARITE offers a Candidate Referral program, where you'll receive a one-time referral bonus based on the following scale if the referred candidate completes a three-month assignment with VARITE.

Experience Level Bonus Referral: 0-2 years

INR 5,000

2-6 years

INR 7,500

6+ years

INR 10,000

About VARITE: VARITE is a global staffing and IT consulting company providing technical consulting and team augmentation services to Fortune 500 Companies in USA, UK, CANADA and INDIA. VARITE is currently a primary and direct vendor to the leading corporations in the verticals of Networking, Cloud Infrastructure, Hardware and Software, Digital Marketing and Media Solutions, Clinical Diagnostics, Utilities, Gaming and Entertainment, and Financial Services.

Equal Opportunity Employer:

VARITE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, marital status, veteran status, or disability status.