Machine Learning Engineer

JOB TITLE: Machine Learning Engineer

DEPARTMENT: Software Development

REPORTS TO: Project Director

PURPOSE:

We are looking for an experienced Machine Learning Engineer to join our team and contribute to the development of robust, scalable models that solve real-world problems. If you are passionate about using data to uncover insights, optimize systems, and enhance user experiences, this role offers the opportunity to work on high-impact projects and shape the future of AI.

KEY RESPONSIBILTIES:

• Develop Predictive Models: Design and implement machine learning models for predictive analytics, utilizing historical data to forecast trends, behaviors, and outcomes.
• Recommendation Engines: Build and optimize personalized recommendation systems using user behavior data and content, employing techniques such as collaborative filtering, matrix factorization, and hybrid systems.
• Speech and Audio Processing: Create and improve models for speech recognition, audio classification, and natural language understanding (NLP) in voice-based applications, leveraging advanced speech and audio processing techniques.
• Data Preprocessing and Feature Engineering: Work with large, complex datasets, implementing best practices for data preprocessing, feature extraction, and feature engineering to optimize model performance.
• Model Deployment and Monitoring: Deploy machine learning models into production environments and manage their lifecycle, ensuring high performance and continuous model improvement through regular evaluation and tuning.
• Collaboration with Cross-Functional Teams: Work closely with data scientists, data engineers, and product teams to align on project goals, ensure data availability, and deliver machine learning-driven solutions.
• Innovation and Knowledge Sharing: Stay up-to-date on the latest machine learning trends and technologies, applying innovative techniques to improve model performance and efficiency. Contribute to internal documentation and knowledge-sharing efforts.
• Documentation and Reporting: Prepare clear and comprehensive documentation on model design, training processes, deployment workflows, and monitoring protocols.
• Cloud Platforms & ML Services: Experience working with cloud platforms such as AWS, Google Cloud, or Azure, and using machine learning services like SageMaker, Google AI Platform, or Azure ML.
• Big Data Technologies: Familiarity with big data technologies like Spark or Hadoop for handling and processing large datasets.
• Audio Processing & NLP Tools: Knowledge of tools such as Librosa, SpeechRecognition, and NLP frameworks like Hugging Face or SpaCy.
• Model Evaluation & Interpretability: Understanding of A/B testing, model evaluation metrics, and interpretability tools such as SHAP and LIME.

QUALIFICATIONS, SKILLS, AND EXPERIENCE:

• At least Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field.
  
• 4-6 years of experience in developing machine learning models, with a strong focus on predictive analytics, recommendation systems, and speech/audio processing.
• Solid understanding of machine learning algorithms, including regression, time series forecasting, ensemble methods, and recommendation systems (e.g., collaborative filtering, matrix factorization, hybrid systems).
• Proficiency in Python (NumPy, Pandas) and SQL for data manipulation, processing, and feature engineering.
• Experience deploying models to production environments and managing the full machine learning lifecycle (from development to deployment and monitoring).