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Machine Learning Engineer

3 months ago

Sahibzada Ajit Singh Nagar, India Alkye Full time

About Us: At Alkye, we are at the forefront of the digital and technology industry, creating innovative solutions that drive business success. Our team is passionate about leveraging the power of machine learning and AI to solve complex problems and enhance our product offerings. We are looking for a dedicated and talented Machine Learning Engineer to join our dynamic team. If you are eager to learn, grow your skills, and make a meaningful impact, we want to hear from you

Job Summary: As a Machine Learning Engineer at Alkye, you will be responsible for developing, deploying, and optimizing machine learning models that power our innovative products and solutions. You will collaborate with cross-functional teams to bring machine learning prototypes into production, ensuring they are scalable, efficient, and integrated seamlessly with our systems.

Key Responsibilities:

  • Model Development and Deployment: Design, develop, and deploy machine learning models and algorithms to solve business challenges and enhance user experiences.
  • Pipeline Management: Build and maintain robust end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and validation.
  • Optimization and Tuning: Optimize and tune models for performance, scalability, and reliability to ensure they meet production standards.
  • Collaboration: Work closely with data scientists, software engineers, and product teams to translate research prototypes into production-ready models.
  • Model Monitoring: Implement best practices for model versioning, testing, and monitoring in production to ensure ongoing accuracy and efficiency.
  • Continuous Learning: Stay up-to-date with the latest advancements in machine learning and AI, and apply new techniques to improve our models and processes.
  • Documentation and Support: Document processes and models, and provide technical support and guidance to other teams as needed.

Qualifications:

  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent practical experience.
  • Skills and Experience:
  • 4+ years of experience in machine learning, data science, or a related field.
  • Proficiency in programming languages such as Python, Java, or C++.
  • Experience with machine learning frameworks like TensorFlow, PyTorch, Keras, and libraries such as scikit-learn.
  • Strong understanding of algorithms, data structures, and software engineering principles.
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and tools like Docker, Kubernetes.
  • Experience with version control systems like Git and CI/CD pipelines.
  • Strong problem-solving skills and attention to detail.
  • Ability to work effectively in a team environment and communicate clearly with colleagues.

Preferred Qualifications:

  • Experience with RESTful APIs and integration.
  • Basic knowledge of MLOps practices, including model monitoring and retraining.
  • Exposure to big data technologies like Spark, Hadoop, or similar.
  • Familiarity with deep learning architectures and applications.

Why Join Us?

  • Innovative Environment: Work with a forward-thinking team that values creativity and new ideas, particularly in the rapidly evolving field of machine learning.
  • Professional Growth: Opportunities for continuous learning and career advancement, including access to the latest tools and technologies in machine learning.
  • Collaborative Culture: Be part of a supportive and inclusive team that encourages collaboration and innovation across disciplines.
  • Competitive Benefits: Enjoy a comprehensive benefits package, including health insurance, retirement plans, and paid time off, to support your well-being and work-life balance.

How to Apply:

  • Alkye is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
  • This job description incorporates the company’s focus on innovation, collaboration, and professional growth, tailored for the role of an ML Engineer.