Role : Lead AI/ML Engineer
REMOTE.
Note : Must have Minimum 12+ years of experience. The candidate must have 12+ years of experience and strong ML fundamentals, Hands-on experience on GenAI and RAG. On the other hand were looking for good engineering skills (Python, Docker etc.) and exposure to cloud technologies is a Description :
- Experience with Pattern Recognition and Neural Networks.
- Proficiency in Statistics and data analysis.
- Excellent knowledge of Python programming for AI and ML applications.
- Ability to work independently and remotely.
- Effective communication and presentation skills.
- Experience in deploying machine learning models in production is a plus.
We are looking for a highly experienced Lead Machine Learning Engineer with 12-15 years of experience in AI, ML, and data science. This remote role involves designing, developing, and deploying cutting-edge machine learning models and AI solutions. The ideal candidate must have expertise in neural networks, pattern recognition, statistics, and Python programming for AI/ML applications. This role requires collaboration with cross-functional teams, integration of AI/ML models into real-world applications, and creating detailed Responsibilities :
- Apply deep learning techniques, including neural networks and pattern recognition, to solve complex problems.
- Conduct data analysis and feature engineering to improve model accuracy.
- Stay updated on latest AI/ML research and integrate state-of-the-art techniques.
- Develop efficient algorithms for AI and machine learning applications.
- Optimize training and inference pipelines for performance and scalability.
- Apply statistical techniques and probability models to enhance model predictions.
- Implement CI/CD pipelines for ML models to automate training and deployment.
- Deploy ML models in production environments using Docker, Kubernetes, and cloud platforms (AWS, Azure, GCP).
- Monitor and maintain deployed models for drift detection, performance tuning, and retraining.
- Work with structured and unstructured data for data preprocessing, cleaning, and augmentation.
- Collaborate with data engineers to ensure smooth ETL pipeline integration for AI models.
- Utilize big data technologies such as Apache Spark, Dask, or Hadoop for large-scale processing.
- Work closely with software engineers, product teams, and business stakeholders to integrate AI/ML solutions.
- Write clear and comprehensive technical documentation on AI models, methodologies, and processes.
- Communicate findings through presentations, reports, and research papers.
Required Skills & Qualifications :
- Strong foundation in Computer Science, Algorithms, and Data Structures.
- Expertise in Pattern Recognition, Neural Networks (CNN, RNN, LSTMs, Transformers), and Deep Learning.
- Proficiency in Statistics, Probability, and Mathematical Optimization.
- Advanced programming skills in Python (NumPy, Pandas, Scikit-Learn, TensorFlow, PyTorch, Keras).
- Experience in deploying ML models using Docker, Kubernetes, and cloud platforms (AWS SageMaker, Azure ML, Google Vertex AI).
- Familiarity with MLOps tools like MLflow, Kubeflow, and Airflow for pipeline automation.
- Strong experience in NLP, Computer Vision, or Reinforcement Learning is a plus.
- Ability to work independently in a remote setting and deliver results.
- Ph.D. or Masters degree in Computer Science, Statistics, AI/ML, or a related field (preferred).
(ref:hirist.tech)