Software Developer (AI Specialist)
Company Overview
We are a forward-thinking technology company dedicated to leveraging artificial intelligence to solve complex problems and drive innovation. Our mission is to deliver cutting-edge AI-driven solutions that transform industries and empower our clients. Join our dynamic team to work on impactful projects in a collaborative and innovative environment.
Job Summary
We are seeking a highly skilled Software Developer with deep expertise in Artificial Intelligence (AI) to design, develop, and deploy advanced AI-driven applications. The ideal candidate will have a strong background in machine learning, deep learning, and software engineering, with a proven ability to build scalable, high-performance systems. This role will involve working closely with cross-functional teams to integrate AI models into production environments and contribute to the full software development lifecycle.
Key Responsibilities
Model Development: Design, develop, and optimize machine learning and deep learning models for tasks such as natural language processing (NLP), computer vision, predictive analytics, or reinforcement learning.
System Integration: Integrate AI models into production systems, ensuring scalability, reliability, and performance in real-world applications.
Software Engineering: Write clean, maintainable, and efficient code in languages such as Python, Java, or C to support AI-driven applications.
Data Pipeline Development: Build and maintain data pipelines for preprocessing, feature engineering, and model training, ensuring data quality and efficiency.
Model Deployment: Deploy AI models using cloud platforms (e.g., AWS, Azure, GCP) or on-premises infrastructure, leveraging tools like Docker, Kubernetes, or serverless architectures.
Performance Optimization: Optimize AI models for inference speed, memory usage, and computational efficiency, including techniques like model pruning, quantization, and distributed computing.
Collaboration: Work with data scientists, product managers, and other engineers to define requirements, translate business needs into technical solutions, and deliver end-to-end AI products.
Research and Innovation: Stay current with the latest advancements in AI, machine learning, and software development, and apply cutting-edge techniques to enhance our products.
Testing and Validation: Implement rigorous testing frameworks to validate model accuracy, robustness, and performance in production environments.
Documentation: Document code, models, and processes to ensure maintainability and knowledge sharing within the team.
Qualifications
Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. A Ph.D. is a plus but not required.
Experience:
3+ years of professional software development experience, with at least 2 years focused on AI or machine learning projects.
Proven track record of building and deploying AI models in production environments.
Technical Skills:
Programming Languages: Proficiency in Python (required), with experience in Java, C, or JavaScript as a plus.
AI/ML Frameworks: Deep expertise in TensorFlow, PyTorch, scikit-learn, or similar frameworks.
Cloud Platforms: Experience with AWS, Azure, or Google Cloud for model deployment and data processing.
Data Tools: Familiarity with data processing tools like Pandas, NumPy, or Apache Spark.
DevOps Tools: Knowledge of Docker, Kubernetes, CI/CD pipelines, and version control systems (e.g., Git).
APIs: Experience integrating AI models with APIs (e.g., REST, gRPC) for real-time applications.
Big Data: Familiarity with big data technologies (e.g., Hadoop, Kafka) is a plus.
Domain Knowledge: Strong understanding of machine learning concepts (e.g., supervised/unsupervised learning, neural networks, transformers, reinforcement learning) and their practical applications.
Soft Skills: Excellent problem-solving skills, strong communication, and ability to work collaboratively in a fast-paced, team-oriented environment.
Preferred Qualifications
Experience with generative AI models (e.g., GPT, Stable Diffusion) or large language models (LLMs).
Familiarity with MLOps practices, including model monitoring, retraining pipelines, and A/B testing in production.
Knowledge of computer vision techniques (e.g., OpenCV, CNNs) or NLP techniques (e.g., BERT, tokenization).
Contributions to open-source AI projects or publications in AI-related fields.
Experience with real-time or edge AI deployment (e.g., TensorRT, ONNX).
Benefits
Competitive salary and equity options.
Comprehensive health, dental, and vision insurance.
Flexible work arrangements, including hybrid or remote options.
Professional development opportunities, including conference attendance and training.
Collaborative and inclusive company culture with regular team-building activities.
