Senior Machine Learning
4 weeks ago
We are seeking a highly skilled and experienced Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will play a crucial role in developing, deploying, and maintaining cutting-edge machine learning models across various domains. You will work closely with data scientists, software engineers, and other cross-functional teams to build scalable and high-performance machine learning solutions that drive business impact.
Roles & Responsibilities:
1. Machine Learning Model Development:
- Utilize your extensive experience to design, develop, and implement state-of-the-art machine learning models.
- Lead and guide the development of complex models, ensuring accuracy, scalability, and efficiency.
2. Python Programming:
- Demonstrate a strong proficiency in Python, using relevant libraries and frameworks for machine learning and deep learning, such as TensorFlow, PyTorch, scikit-learn, and Keras.
- Write efficient, clean, and scalable code for model development, evaluation, and optimization.
3. Model Deployment and Productionization:
- Leverage your expertise to deploy machine learning models to production systems efficiently.
- Manage the end-to-end process of model deployment, including data preprocessing, model training, optimization, and integration into production environments.
4. Model Engineering and Improvement:
- Enhance model accuracy through advanced engineering techniques, including feature engineering, feature selection, and data augmentation.
- Analyze model samples in relation to model scores, identify patterns, and iteratively refine models for improved performance.
5. Cloud Computing:
- Utilize cloud computing platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, for scalable and cost-effective model deployment.
- Leverage cloud services for data storage, compute resources, and orchestration to optimize model performance.
6. Advanced Model Types:
- Apply your knowledge and practical experience with advanced model types, such as deep learning architectures (e.g., convolutional neural networks, recurrent neural networks), generative AI models (e.g., GANs), and natural language processing (NLP) techniques.
7. Version Control and Model Management:
- Employ version control systems (e.g., Git, Stash) and best practices for managing different versions of machine learning models.
- Ensure model versioning, tracking, and reproducibility for seamless collaboration within the team.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
- 5+ years of hands-on experience in developing and implementing machine learning models across diverse domains.
- Must be willing to work 2pm- 10pm IST to overlap with EST stakeholders/business partners
- Proficient in Python programming, with a deep understanding of relevant machine learning libraries and frameworks.
- Proven experience in deploying machine learning models to production environments.
- Strong engineering skills for improving model accuracy and performance.
- Familiarity with cloud computing platforms and their services for scalable model deployment.
- Knowledge of advanced machine learning techniques, including deep learning and NLP.
- Experience with version control systems and model management tools.
- Strong problem-solving abilities and an analytical mindset.
- Excellent communication and collaboration skills to work effectively in a team-oriented environment.
Join our dynamic team, where you will have the opportunity to work on challenging projects that make a significant impact on our organization and the industry. We offer competitive compensation, a flexible work environment, and opportunities for professional growth and development. If you are passionate about machine learning and love solving complex problems, we would love to hear from you
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