Machine Learning and Artificial Intelligence
Job Title:
Machine Learning Innovation Lead
Job Overview
As a Machine Learning Innovation Lead, you will be responsible for designing, developing, and deploying AI/ML models that drive business intelligence, automation, and predictive analytics. You will work with large datasets, build scalable ML solutions, and collaborate with cross-functional teams to implement AI-driven strategies that optimize operations and decision-making.
Key Responsibilities
- AI/ML Model Development – Design and implement machine learning models for predictive analytics, recommendation systems, and automation.
- Deep Learning & Neural Networks – Utilize deep learning frameworks such as TensorFlow and PyTorch to develop advanced AI solutions.
- Data Engineering & Feature Engineering – Process and analyze large datasets, create feature pipelines, and optimize data preprocessing techniques.
- Model Deployment & MLOps – Deploy AI models in production environments using cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Natural Language Processing (NLP) & Computer Vision – Work on AI-powered solutions like chatbots, speech recognition, image recognition, and text analytics.
- AI Ethics & Compliance – Ensure AI solutions are explainable, fair, and compliant with industry regulations.
- Collaboration & Research – Stay updated with the latest AI/ML advancements and collaborate with data scientists, engineers, and business teams.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field
- 3+ years of experience in machine learning model development and AI research
- Proficiency in Python, R, or Java for AI/ML development
- Expertise in ML frameworks (TensorFlow, PyTorch, Scikit-learn, Keras)
- Experience with big data technologies (Hadoop, Spark, Snowflake, Databricks)
- Knowledge of cloud-based AI services (AWS SageMaker, Google Vertex AI, Azure ML)
- Familiarity with AI model evaluation, hyperparameter tuning, and performance optimization
Preferred Qualifications
- Certifications in Google Professional ML Engineer, AWS Machine Learning Specialty, or Microsoft AI Engineer
- Experience with Generative AI, Large Language Models (LLMs), or Reinforcement Learning
- Knowledge of Edge AI, AI chipsets (TPUs, NPUs), and IoT-based AI solutions
Job Benefits
- Competitive salary & performance-based bonuses
- Work with cutting-edge AI technologies
- Flexible work environment (remote/hybrid)
- Career advancement opportunities in AI research and innovation