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Weekday AI (YC W21)
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Machine Learning Engineer

Machine Learning Engineer

Weekday AI (YC W21)

4 years

25 - 35 Lacs

Bengaluru Karnataka India

Posted:1 week ago| Platform:

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Skills Required

learning ai ml power data software cutting research algorithms preprocessing vision design engineering analysis model tuning docker mlflow airflow kubernetes code documentation development deployment drive mathematics statistics regression clustering programming python tensorflow pytorch xgboost pipeline automation git collaborative aws sagemaker azure spark hadoop

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 3500000 (ie INR 25-35 LPA)

Min Experience: 4 yearsLocation: BengaluruJobType: full-timeWe are looking for a highly skilled and motivated

Machine Learning Engineer

with 4-6 years of experience to join our growing team. As a core member of our AI/ML division, you will be responsible for designing, developing, deploying, and maintaining machine learning solutions that power real-world products and systems. You'll collaborate with data scientists, software engineers, and product teams to bring cutting-edge ML models from research into production.The ideal candidate will have a strong foundation in machine learning algorithms, statistical modeling, and data preprocessing, along with proven experience deploying models at scale. This role offers the opportunity to work on a variety of projects involving predictive modeling, recommendation systems, NLP, computer vision, and more.

Requirements

Key Responsibilities:

Design and develop robust, scalable, and efficient machine learning models for various business applications.
Collaborate with data scientists and analysts to understand project objectives and translate them into ML solutions.
Perform data cleaning, feature engineering, and exploratory data analysis on large, structured and unstructured datasets.
Evaluate, fine-tune, and optimize model performance using techniques such as cross-validation, hyperparameter tuning, and ensembling.
Deploy models into production using tools and frameworks such as Docker, MLflow, Airflow, or Kubernetes.
Continuously monitor model performance and retrain/update models as required to maintain accuracy and relevance.
Conduct code reviews, maintain proper documentation, and contribute to best practices in ML development and deployment.
Work with stakeholders to identify opportunities for leveraging ML to drive business decisions.

Required Skills and Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field.
4-6 years of hands-on experience in designing and implementing machine learning models in real-world applications.
Strong understanding of classical ML algorithms (e.g., regression, classification, clustering, ensemble methods) and experience with deep learning techniques (CNNs, RNNs, transformers) is a plus.
Proficient in programming languages such as Python (preferred) and experience with ML libraries/frameworks like scikit-learn, TensorFlow, PyTorch, XGBoost, or LightGBM.
Experience in data preprocessing, feature selection, and pipeline automation.
Familiarity with version control systems (e.g., Git) and collaborative development environments.
Ability to interpret model results and communicate findings to technical and non-technical stakeholders.
Strong problem-solving skills and a passion for innovation and continuous learning.

Preferred Qualifications:

Experience with cloud-based ML platforms (AWS SageMaker, Azure ML, or Google Cloud AI Platform).
Exposure to big data technologies (e.g., Spark, Hadoop) and data pipeline tools (e.g., Airflow).
Prior experience in model deployment and ML Ops practices

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Machine Learning Engineer