As an AI/ML Engineer, you will be responsible for developing, optimizing, and deploying machine learning models, as well as leading and contributing to the design of AI-driven solutions. You will work alongside a dynamic team of engineers and data scientists to solve complex challenges using AI/ML techniques. This role requires strong programming skills, a deep understanding of machine learning algorithms, and hands-on experience in applying AI solutions to real-world business problems.
Key Responsibilities:
Model Development & Optimization:
Design, develop, and deploy machine learning models for various applications, including predictive analytics, recommendation systems, natural language processing (NLP), computer vision, and time-series forecasting.
Optimize and fine-tune models to improve accuracy, efficiency, and scalability.
Implement state-of-the-art AI techniques in practical settings.
Data Processing & Analysis:
Work with large datasets, performing data cleaning, feature engineering, and data exploration.
Utilize tools such as Pandas, NumPy, and PySpark to process and analyze structured and unstructured data.
Collaboration & Leadership:
Collaborate with cross-functional teams (product, business, and engineering) to define AI/ML solutions that meet business requirements.
Provide mentorship to junior team members and assist in their professional development.
Lead end-to-end model development, including data collection, training, testing, deployment, and monitoring.
Model Deployment & Scaling:
Work with DevOps and cloud engineering teams to deploy and maintain AI models in production environments.
Utilize tools such as Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure) for model deployment and scaling.
Research & Innovation:
Stay current with the latest developments in AI/ML and explore new methodologies that can be applied to real-world problems.
Drive the innovation and implementation of advanced AI techniques to enhance product offerings and business solutions.
Required Skills and Experience:
Experience: 5-6 years of professional experience in AI/ML development.
Programming Languages: Proficiency in Python, R, or Java. Experience with machine learning libraries like TensorFlow, PyTorch, Scikit-learn, or Keras.
Machine Learning Algorithms: Strong understanding of supervised and unsupervised learning, deep learning, reinforcement learning, and NLP.
Data Handling: Experience working with large datasets, data preprocessing, and feature engineering. Familiarity with SQL, NoSQL, and big data tools (e.g., Hadoop, Spark).
Cloud and Deployment: Experience with cloud computing (AWS, GCP, Azure) and deployment of machine learning models.
Model Evaluation & Tuning: Knowledge of model evaluation techniques (cross-validation, A/B testing) and hyperparameter tuning methods (GridSearch, RandomSearch).
Version Control & Collaboration Tools: Familiarity with Git, JIRA, and Agile development methodologies.
Preferred Qualifications:
Master’s or Ph.D. in Computer Science, Data Science, Engineering, or a related field.
Experience in specific domains like NLP, computer vision, or reinforcement learning.
Familiarity with tools like MLflow, Kubeflow, or other model management frameworks.
Experience with MLOps practices and model monitoring in production.
Why Join Us:
Opportunity to work on cutting-edge AI/ML projects.
Collaborative and inclusive work environment with a strong focus on innovation.
