Machine Learning Solutions Architect
2 days ago
Machine Learning Solutions Architect
About Unreal Gigs:We are a technology-driven company that provides innovative solutions for businesses to drive growth and success.
About the Role:This is an exciting opportunity for an experienced Machine Learning Solutions Architect to join our team at Unreal Gigs. We're looking for someone with a strong background in machine learning engineering, who can design and deploy scalable and efficient models that meet business objectives.
Responsibilities:- Design and Develop Machine Learning Models: Build, train, and deploy machine learning models using frameworks such as TensorFlow, PyTorch, or Scikit-learn. Develop models for applications like recommendation systems, predictive analytics, and natural language processing (NLP).
- Data Collection, Cleaning, and Preprocessing: Collaborate with data engineers and analysts to collect, clean, and prepare large datasets for training and evaluation. Design data pipelines that automate the preprocessing steps, ensuring the data is ready for model training.
- Model Training and Hyperparameter Tuning: Train machine learning models and perform hyperparameter optimization to improve model performance. Experiment with different algorithms, evaluate model accuracy, and optimize results based on business needs.
- Deployment and Integration: Work closely with software engineers to deploy machine learning models into production environments. Build APIs, integrate models into existing systems, and ensure models are scalable, maintainable, and easily accessible by applications.
- Model Monitoring and Maintenance: Continuously monitor the performance of deployed models and retrain or fine-tune them as needed to maintain accuracy and relevance. Establish systems to detect model drift and ensure that models adapt to new data over time.
- Collaboration and Cross-Functional Support: Partner with data scientists, software engineers, and product managers to identify opportunities for machine learning solutions that drive business objectives. Translate business problems into technical solutions, working across departments to deliver impactful results.
- Machine Learning Expertise: Strong knowledge of machine learning algorithms such as regression, classification, clustering, deep learning, and reinforcement learning. Proficient with frameworks like TensorFlow, PyTorch, and Scikit-learn.
- Programming Skills: Proficiency in programming languages such as Python, R, or Java. Hands-on experience with data manipulation libraries like Pandas, NumPy, or Spark and can write clean, efficient code.
- Data Engineering: Experience in handling large datasets, feature engineering, and data preprocessing. Know how to clean, normalize, and transform raw data to make it suitable for model training.
- Model Deployment: Familiarity with deploying machine learning models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker or Kubernetes.
- Performance Optimization: Strong ability to fine-tune models for performance and optimize algorithms for scalability and speed, ensuring models are robust in production environments.
- Competitive Salary: $120,000 - $180,000 per year, depending on experience.
- Comprehensive Benefits: Health, dental, and vision insurance plans, 401(k) matching, paid time off, and professional development opportunities.
- Culture: Collaborative, dynamic work environment with a focus on innovation and teamwork.
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