Syren Technologies - Machine Learning Engineer

About the job :

Key Responsibilities :

Model Development :

- Design, build, train, and optimize machine learning models using state-of-the-art techniques.

- Conduct exploratory data analysis to identify patterns and inform feature engineering.

Data Pipeline Management :

- Collaborate with data engineers to build robust, scalable, and efficient data pipelines.

- Ensure data quality, preprocessing, and cleaning for ML model input.

Deployment & Monitoring :

- Deploy ML models to production environments using MLOps practices.

- Monitor and evaluate the performance of models in production, iterating to improve accuracy and efficiency.

Collaboration & Integration :

- Work with cross-functional teams to integrate ML models into existing products and services.

- Translate business problems into machine learning solutions.

Research & Innovation :

- Stay updated with the latest advancements in machine learning and AI.

- Experiment with new tools, algorithms, and frameworks to continuously improve processes.

Documentation & Communication :

- Document model development, data processes, and experiments for reproducibility.

- Communicate findings and technical details to both technical and non-technical stakeholders.

Qualifications :

Must-Have :

- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.

- Proven experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

- Proficiency in programming languages such as Python, Java, or Scala.

- Strong understanding of algorithms, statistics, and applied mathematics.

- Experience with cloud platforms (AWS, Azure, GCP) for ML model deployment.

Nice-to-Have :

- Familiarity with MLOps tools like MLflow, Kubeflow, or Airflow.

- Knowledge of big data tools like Apache Spark or Hadoop.

- Understanding of deep learning, NLP, or computer vision.

- Experience with containerization and orchestration tools like Docker and Kubernetes