Sr. Machine Learning Engineer

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   Location:  Onsite, Remote, Hybrid