
AIML Engineer
2 weeks ago
We're looking for a highly skilled
AI/ML Engineer
to design, develop, and deploy advanced machine learning solutions that solve complex business challenges. You'll work closely with cross-functional teams—Data Engineers, Product Managers, and Software Developers—to bring AI-powered features and insights into production-ready systems.
Key Responsibilities
- Design & Develop ML Models:
Build, train, and optimize machine learning and deep learning models for real-world applications (e.g., NLP, computer vision, recommendation systems). - Data Preparation & Feature Engineering:
Collect, clean, and preprocess large-scale datasets for model development. - Deployment & Integration:
Package models into APIs or services, deploy to cloud platforms (AWS, Azure, GCP), and ensure scalability and reliability. - Monitor & Maintain Models:
Track model performance in production, retrain as needed, and manage version control. - Collaboration:
Partner with product and engineering teams to translate business requirements into technical solutions. - Innovation:
Research and implement cutting-edge ML algorithms and tools to improve existing processes and products.
Required Skills & Experience
- 5–8 years of experience in AI/ML development and deployment.
- Proficiency in
Python
(pandas, NumPy, scikit-learn) and at least one deep learning framework (
TensorFlow
or
PyTorch
). - Strong understanding of algorithms, statistics, and machine learning techniques (e.g., regression, classification, clustering, CNNs, RNNs).
- Experience with
cloud platforms
(AWS SageMaker, Azure ML, or GCP AI Platform). - Familiarity with
data engineering concepts
(ETL, data pipelines, SQL/NoSQL databases). - Hands-on experience deploying ML models in production environments (e.g., REST APIs, Docker, Kubernetes).
- Solid problem-solving skills and the ability to work in an agile, fast-paced environment.
Preferred Qualifications
- Exposure to
MLOps
practices (CI/CD for ML, model monitoring, automated retraining). - Experience with
natural language processing (NLP)
or
computer vision
projects. - Knowledge of big data tools like
Spark
or
Hadoop
. - Master's degree in Computer Science, Data Science, or a related field.
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