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AI Innovation Engineer
hace 2 meses
Job Title: AI Innovation Engineer
Job Type: Full-Time
Location: Remote
Company Overview:
Mechanized AI is a pioneering organization in AI innovation, leveraging cutting-edge technology to transform legacy systems into modern, efficient, and scalable solutions. We collaborate with enterprise clients to breathe life into their existing software, ensuring they can meet the demands of today's fast-paced, digital landscape.
Job Summary:
We are seeking an experienced AI Innovation Engineer to join our growing team. The ideal candidate will have a background in Machine Learning (ML) with at least four years of experience outside of academia.
Key Responsibilities:
- Contribute to building and enhancing our Mechanized AI platform and AI-enabled products.
- Serve as ML SME on client projects as needed.
- Design ML systems.
- Research and implement appropriate ML algorithms and tools.
- Select appropriate datasets and data representation methods.
- Run ML tests and experiments.
- Perform statistical analysis and fine-tuning using test results.
- Train and retrain systems when necessary.
- Extend existing ML libraries and frameworks.
- Stay current with emerging technologies and ML best practices to continuously improve our methodologies and tools.
Required Skills & Experience:
- 4+ years of ML experience at a start-up or larger enterprise.
- 6+ months of experience with Large Language Models (LLMs) and Generative AI (GenAI) applications.
- Client delivery experience.
- Effective written and oral communications skills (C1/C2 - advanced/proficient level English is required).
- Bachelor's degree in computer science, software engineering, or related field.
- Experience with cloud environments (e.g., AWS, Azure, GCP).
- Experience with ML frameworks and libraries (TensorFlow, PyTorch, Keras, scikit-learn).
- Experience developing, deploying, and managing/monitoring models.
- Knowledge of containerization technologies (e.g., Docker, Kubernetes) and microservices architecture.
- Expertise in Object-Oriented Programming (OOP) principles and unit test-driven development methodologies.
- Advanced experience in NLP techniques and applications.
- Strong proficiency in Python programming.
- Familiarity with prompt engineering approaches and best practices.
- Knowledge of data structures, data modeling, and software architecture.
- Strong analytical and problem-solving skills, with ability to propose innovative solutions and troubleshoot issues.
- Ability to work independently and as part of a collaborative team in a fast-paced environment.
Preferred Qualifications:
Experience in any of the following:
- Agent development.
- Data privacy.
- Fine tuning LLMs.
- LLM architecture and techniques for performance.
- MLOps.
- ML evaluation.
- Model decay and data drift detection and handling.
- Pulumi, Terraform, and/or Cloud SDKs.
- PySpark.
- Quantization.
- Retrieval-augmented generation (RAG) optimization.
- Security.
- Vector databases.
