Machine Learning Engineer

Lead ML Engineer - SearchUnify

About the Role: Join our innovative SearchUnify team as a Lead ML Engineer, where you will spearhead the development and deployment of cutting-edge machine learning solutions. This role offers an exceptional opportunity for both emerging talent and seasoned professionals to drive impactful advancements in search and knowledge management technologies, shaping the future of how users interact with information.

**Responsibilities:**

• Design, develop, and implement robust machine learning models and algorithms to enhance search relevance, personalization, and knowledge discovery.
• Lead the end-to-end machine learning lifecycle, from data ingestion and feature engineering to model training, evaluation, and deployment in production environments.
• Collaborate closely with product managers, software engineers, and data scientists to translate business requirements into scalable ML solutions.
• Conduct research and stay abreast of the latest advancements in machine learning, artificial intelligence, and natural language processing, applying them to improve existing products and identify new opportunities.
• Mentor and guide junior ML engineers, fostering a culture of technical excellence, knowledge sharing, and continuous learning within the team.
• Develop and maintain robust MLOps practices, including CI/CD pipelines for ML models, monitoring, and version control to ensure reliability and scalability.
• Analyze large datasets to extract insights, identify patterns, and inform the development of more effective ML strategies and features. **Requirements:**
• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related quantitative field.
• Proven experience (0-10 years) in developing and deploying machine learning models, with a strong understanding of core ML concepts and algorithms.
• Proficiency in at least one major programming language such as Python, Java, or Scala, and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with data manipulation and analysis tools (e.g., Pandas, SQL) and experience working with large datasets.
• Excellent problem-solving skills, a strong analytical mindset, and the ability to work independently and as part of a team.
• Demonstrated ability to learn quickly, adapt to new technologies, and contribute effectively in a fast-paced environment.

**Nice to Have:**

• Experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Knowledge of big data technologies (e.g., Spark, Hadoop).
• Familiarity with Natural Language Processing (NLP) techniques and libraries (e.g., NLTK, spaCy).
• Experience with MLOps tools and practices for model deployment and monitoring.