Machine Learning Engineer

JOB TITLE:Machine Learning EngineerDEPARTMENT:Software DevelopmentREPORTS TO:Project DirectorPURPOSE: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).#J-18808-Ljbffr