AI/ML Engineer

• Develop, train, and deploy machine learning models to solve real-world problems.
• Design and implement scalable AI/ML pipelines, from data preprocessing to model deployment.
• Collaborate with data engineers and backend teams to integrate models into production systems.
• Optimize algorithms and models for performance, accuracy, and efficiency.
• Conduct exploratory data analysis to uncover insights and inform model development.
• Stay up-to-date with the latest AI/ML advancements and apply them to enhance project outcomes.
• Troubleshoot and refine models with minimal guidance, ensuring robustness and reliability.

Job Requirements/Skills

• 3-5 years of experience in AI/ML development, with a focus on practical applications.
• Strong proficiency in Python and libraries such as TensorFlow, PyTorch, scikit-learn, or Keras.
• Experience with data manipulation tools (e.g., Pandas, NumPy) and working with large datasets.
• Knowledge of supervised and unsupervised learning techniques, NLP, or computer vision (depending on project needs).
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) for model training and deployment.
• Ability to work independently, prioritize tasks, and deliver high-quality results with minimal oversight.
• Solid understanding of software engineering principles and version control (e.g., Git).
• Excellent analytical skills and a strong foundation in statistics and mathematics.

Preferred Qualifications

• Experience with MLOps tools (e.g., MLflow, Kubeflow) or containerization (e.g., Docker).
• Familiarity with big data frameworks like Spark or Hadoop.
• Prior work in deploying AI models in production environments or real-time systems.
• Exposure to Agile methodologies or cross-functional team settings.

Key Skills

• Machine Learning Model Development
• Python & AI Libraries (TensorFlow, PyTorch, etc.)
• Data Manipulation & Large Datasets
• Supervised & Unsupervised Learning
• Cloud Platforms (AWS, GCP, Azure)
• MLOps & Containerization