Senior AI Engineer
4 weeks ago
We are seeking a highly skilled Senior AI Engineer to design, develop, and deploy advanced AI/ML solutions that solve complex business challenges and power next-generation products. The ideal candidate has strong expertise in machine learning, deep learning, and generative AI, with proven experience building scalable systems in production environments.
As a senior member of the team, you will play a hands-on technical role while also mentoring junior engineers, contributing to architectural decisions, and collaborating with cross-functional teams to integrate AI into real-world applications.
Key Responsibilities:
AI/ML Solution Development
- Design, build, and optimize machine learning and deep learning models (supervised, unsupervised, reinforcement learning, generative AI).
- Implement end-to-end pipelines, including data ingestion, preprocessing, model training, evaluation, and deployment.
- Work with large datasets, structured and unstructured, applying feature engineering and advanced ML techniques.
- Research and prototype cutting-edge AI methods (LLMs, RAG, multimodal AI, computer vision, NLP).
Systems Engineering & Deployment
- Develop scalable, production-grade AI services and APIs.
- Apply MLOps best practices: model versioning, CI/CD pipelines, monitoring, and retraining workflows.
- Optimize models for latency, scalability, and cost efficiency in cloud (AWS, Azure, GCP) or hybrid environments.
- Ensure solutions are secure, resilient, and compliant with data governance standards.
Collaboration & Leadership
- Partner with data scientists, product managers, and software engineers to translate business needs into AI solutions.
- Mentor junior engineers and contribute to building a high-performance AI engineering culture.
- Influence architectural decisions on AI/ML platforms, frameworks, and tools.
- Contribute to technical documentation, design reviews, and coding best practices.
Innovation & Continuous Learning
- Stay current with AI research, frameworks, and tools, and assess their potential adoption.
- Experiment with generative AI and emerging technologies to enhance organizational capabilities.
- Advocate for responsible and ethical AI practices.
Qualifications & Experience:
- Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related field (PhD preferred).
- 5–8 years of experience in AI/ML engineering with a proven track record of delivering production systems.
- Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, JAX).
- Proficiency in Python (and optionally C++/Java for performance-critical components).
- Strong background in data engineering (SQL/NoSQL, Spark, Kafka, or similar).
- Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
- Strong knowledge of MLOps tools (Kubeflow, MLflow, Airflow, Docker, Kubernetes).
- Expertise in NLP, computer vision, or generative AI is highly desirable.
- Familiarity with vector databases (Pinecone, Weaviate, FAISS) and RAG architectures.
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