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Sr. Machine Learning Engineer

Cloud Counselage Pvt Ltd · Удалённо · India

# Sr. Machine Learning Engineer **Cloud Counselage Pvt Ltd** · India · `Remote` · `Full Time` 💼 **Уровень роли:** `Senior` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Machine-Learning-Engineer]` `[Senior-ML-Engineer]` `[AI-Engineer]` `[Data-Scientist]` `[Senior-AI-ML-Engineer]` `[Senior-ML-Engineering]` `[Senior-Applied-ML-Engineer]` --- ### About the Role TO GET TIMELY UPDATES ON JOB OPENINGS, FEEL FREE TO JOIN OUR COMMUNITY @ (4L+ MEMBERS FROM 35+ COUNTRIES) Job Overview: Looking for a highly skilled Senior Machine Learning Engineer to join our team. As a Senior ML Engineer, you will play a key role in developing and deploying cutting-edge machine learning models and algorithms to solve complex business problems. You will work closely with cross-functional teams to design, implement, and optimize ML solutions that drive business impact. Responsibilities: - Research, design, and implement machine learning algorithms and models to solve business challenges - Collaborate with data scientists and domain experts to gather requirements, analyze data, and validate hypotheses - Develop scalable and efficient machine learning pipelines for data preprocessing, feature engineering, model training, and evaluation - Design and implement experiments to evaluate model performance, interpret results, and iterate on models to improve accuracy and efficiency - Deploy machine learning models into production systems and monitor their performance in real-world applications - Work closely with software engineers to integrate machine learning models into existing systems and develop new features - Stay up-to-date with the latest advancements in machine learning research and apply them to solve business problems effectively - Mentor junior team members and provide technical guidance on best practices in machine learning development and deployment Mandatory Requirements: - Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field. Advanced degree (MS/PhD) preferred - 4-7 years of experience in machine learning, data science, or a related field, with a proven track record of developing and deploying machine learning models in production environments - Strong programming skills in Python and proficiency in machine learning libraries such as TensorFlow, PyTorch, or scikit-learn - Experience with big data technologies such as Apache Spark for data processing and distributed computing - Solid understanding of machine learning algorithms, statistical methods, and deep learning techniques - Experience with cloud platforms such as AWS, Azure, or GCP, and familiarity with deploying ML models using containerization technologies (Docker, Kubernetes) - Excellent problem-solving skills and ability to work independently as well as part of a team in a fast-paced environment - Strong communication skills with the ability to explain complex concepts and findings to both technical and non-technical stakeholders Preferred Requirements: - Experience with natural language processing (NLP) or computer vision (CV) applications - Knowledge of reinforcement learning techniques and their applications - Familiarity with version control systems (e.g., Git) and agile software development methodologies Benefits: - Competitive salary and benefits package - Opportunities for professional development and career advancement - Exposure to cutting-edge technologies and industry best practices - Dynamic and collaborative work environment - Potential for remote work options and flexible work hours Job Location: Remote/Hybrid/In-Office Note: To accomplish our vision, our Flagship Event ' IAC VISION 2030 ' would provide employment and career opportunities for millions of job-ready interns, freshers and professionals in our Industry Academia Community (IAC). By submitting your application you accept the Terms and Conditions. Originally posted on Himalayas

Наблюдалась 2026-10-16, впервые 2026-10-16, источник — Himalayas (JSON API).

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