AL/ML Engineer

Job Summary

Roles And Responsibilities

• Design, develop, and deploy machine learning models for various applications.
• Work with large datasets, perform data cleaning, preprocessing, and feature engineering.
• Analyze data to extract insights and identify patterns, trends, and relationships.
• Implement machine learning models into production environments.
• Maintain and improve deployed models over time.
• Communicate complex technical concepts and results to both technical and non-technical audiences.
• Stay updated with the latest advancements in AI/ML technologies.
• Propose and implement innovative AI/ML solutions to solve complex business problems.
• Document models, processes, and systems for knowledge transfer and reproducibility.

Required Skills And Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related field.
• Proficiency in Python and/or R; experience with libraries such as TensorFlow, PyTorch, Scikit-learn, etc.
• Experience with SQL and NoSQL databases; familiarity with big data tools such as Hadoop, Spark, or similar.
• Strong understanding of supervised, unsupervised, and reinforcement learning techniques.
• Hands-on experience with neural networks, CNNs, RNNs, LSTMs, etc.
• Experience with ML frameworks like TensorFlow, Keras, PyTorch, or similar.
• Familiarity with cloud services like AWS, Google Cloud, Azure for deploying AI/ML models.
• Experience with Git or other version control systems.
• Experience in developing and integrating RESTful APIs for ML model deployment.
• Strong problem-solving abilities and the ability to work with complex datasets.
• Able to translate business requirements into technical solutions.
• Excellent verbal and written communication skills.
• Able to work in a collaborative, team-oriented environment.
• Proven ability to handle multiple projects simultaneously.
• 2+ years of experience in AI/ML engineering or a related field.
• Proven track record of deploying ML models into production.

Additional Preferred Qualifications And Certifications

• Experience with MLOps practices and tools.
• Experience with natural language processing (NLP) and computer vision.
• Published research in the field of AI/ML.
• Experience with containerization technologies such as Docker and Kubernetes.

Why Join Us?

• Innovative Environment: Work on cutting-edge projects with the latest AI/ML technologies.
• Career Growth: Opportunities for professional development and career advancement.
• Collaborative Culture: Work in a supportive and inclusive team environment.
• Impact: Contribute to meaningful projects that make a difference.

How To Apply

Interested candidates are invited to submit their resume and a cover letter detailing their qualifications and experience. Please include examples of past projects or links to your GitHub profile.