AI/ML Engineer

Job Title: AI/ML Engineer
Location: Remote
Job Type: Full-Time
Experience Level: 7 Years

Job Description:
We are looking for a talented and experienced AI/ML Engineer to develop advanced machine learning models, algorithms, and AI systems. You will work closely with cross-functional teams to build, deploy, and optimize AI-driven products that enhance our business solutions.

Responsibilities:
AI/ML Model Development: Design, implement, and optimize machine learning algorithms and models for real-world applications.
Data Analysis and Preprocessing: Work with large datasets, clean and preprocess data, and perform exploratory data analysis (EDA) to extract meaningful insights.
Algorithm Optimization: Continuously improve model performance through hyperparameter tuning, feature engineering, and experimentation with different model architectures.
Model Deployment: Deploy models into production environments, ensuring scalability, performance, and reliability.
Cross-functional Collaboration: Collaborate with data engineers, product managers, and other stakeholders to understand requirements and deliver high-impact AI solutions.
Research and Innovation: Stay updated with the latest trends and advancements in AI/ML, applying new techniques to improve our solutions and drive innovation.
Performance Evaluation: Evaluate model performance, interpret results, and communicate insights and findings to technical and non-technical stakeholders.
Code Quality & Documentation: Write clean, maintainable, and efficient code while documenting processes, models, and workflows for easy collaboration and future reference.

Required Skills:
7+ years of experience in AI/ML engineering with a proven track record of delivering impactful projects.
Strong proficiency in Python, including libraries such as NumPy, Pandas, TensorFlow, PyTorch, scikit-learn, Keras, etc.
In-depth knowledge of machine learning techniques, including supervised, unsupervised, and reinforcement learning.
Hands-on experience with deep learning architectures (CNNs, RNNs, Transformers, etc.).
Expertise in model evaluation and selection, including cross-validation, A/B testing, and performance metrics.
Experience with big data technologies such as Spark, Hadoop, or distributed computing environments.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud, specifically for deploying ML models.
Strong understanding of data preprocessing, feature engineering, and data wrangling techniques.
Experience with model monitoring, A/B testing, and performance optimization in production environments.
Proficiency in SQL for querying and working with large datasets.
Solid understanding of software engineering best practices including version control (Git), unit testing, and CI/CD pipelines.

Preferred Skills:
Experience with natural language processing (NLP), computer vision, or other specialized AI areas.
Advanced degree (MSc, PhD) in Computer Science, Artificial Intelligence, Data Science, or related field.
Experience with containerization technologies like Docker and Kubernetes.
Knowledge of DevOps practices and tools related to ML workflows.
Familiarity with Edge AI and deploying models on devices with limited resources.
Strong communication and presentation skills to convey technical concepts to non-technical stakeholders.