Posted 23 July, 2026
Machine Learning Engineer
VARITE INDIA PRIVATE LIMITED
Noida, Uttar Pradesh, IN
Full Time
Reference: 26-40191-2522-2
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.
About The Job:
Machine Learning & Model Development
Machine Learning
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:
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.
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.
About The Job:
- The Machine Learning Engineer is responsible for designing, developing, deploying, and maintaining machine learning models that support clinical, operational, and business objectives. The role spans the complete machine learning lifecycle, including problem definition, data preparation, feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
- The ideal candidate combines strong machine learning, statistical, programming, and data engineering skills to deliver scalable and production-ready AI solutions.
Machine Learning & Model Development
- Translate business and operational requirements into machine learning use cases and predictive models.
- Develop, train, validate, and optimize machine learning models for classification, regression, forecasting, clustering, and anomaly detection.
- Apply statistical and machine learning techniques to solve complex business problems.
- Perform model tuning, validation, and performance optimization to improve accuracy and reliability.
- Ensure reproducible and well-documented model development practices.
- Source, transform, and prepare large datasets using SQL and Python.
- Build and maintain reliable data pipelines and workflows supporting model development.
- Conduct exploratory data analysis to identify trends, anomalies, and data quality issues.
- Develop clean and validated training, testing, and validation datasets.
- Design and implement meaningful features from structured and semi-structured data.
- Handle data challenges such as missing values, outliers, and class imbalance.
- Collaborate with business and subject matter experts to incorporate domain knowledge into model design.
- Deploy machine learning models into production environments.
- Develop automated ML pipelines for training, validation, deployment, and retraining.
- Monitor model performance, drift, and prediction quality over time.
- Implement model versioning, governance, and documentation standards.
- Integrate model outputs with reporting and analytics platforms such as Power BI.
- Partner with Data Engineering, Analytics, and business stakeholders to define success criteria and measurable outcomes.
- Communicate model results, assumptions, limitations, and recommendations to technical and non-technical audiences.
- Ensure adherence to coding, security, and data governance standards.
Machine Learning
- End-to-end machine learning lifecycle experience.
- Supervised and unsupervised learning techniques.
- Model evaluation, validation, and performance tuning.
- Experience with Scikit-learn, XGBoost, LightGBM, CatBoost, or similar frameworks.
- Strong Python programming skills.
- Experience with Pandas, NumPy, Scikit-learn, and related ML libraries.
- Version control using Git.
- Advanced SQL and data manipulation skills.
- Experience working with large-scale structured and semi-structured datasets.
- Data modeling, ETL/ELT, and pipeline development experience.
- Regression analysis, hypothesis testing, correlation analysis, and statistical inference.
- Understanding of model assumptions and predictive analytics concepts.
- Experience with cloud platforms such as Azure, AWS, or GCP.
- Exposure to MLOps tools and frameworks (MLflow, Azure ML, Databricks, Kubeflow, Airflow).
- Experience with Power BI or enterprise reporting platforms.
- Familiarity with REST APIs and data integration techniques.
- Knowledge of healthcare, clinical, financial, or operational analytics domains.
- Understanding of data governance, model governance, and responsible AI practices.
- Experience with Docker, CI/CD pipelines, and production deployment methodologies.
- Experience: 5–7 years of hands-on experience in Machine Learning, Data Science, or Advanced Analytics.
- Education: Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or a related discipline.
- Proven experience developing and operationalizing machine learning models in production environments.
- Strong analytical, problem-solving, and communication skills.
- Ability to work independently while collaborating effectively with cross-functional teams.
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.
