Job Description:
We are seeking an innovative and results-oriented Mid-Level AI/ML Engineer to join our dynamic team. This role is crucial for transforming novel concepts into robust, production-ready AI solutions. The ideal candidate possesses a strong background in Machine Learning engineering, extensive experience with cutting-edge LLMs and cloud-based AI services, and a commitment to maintaining high-quality, responsible AI systems.
Key Responsibilities
Full ML Lifecycle Management: Drive projects from initial ideation to production deployment, including data pipeline development, model training, validation, and serving.
LLM & Agentic Development: Design, implement, and optimize solutions utilizing Large Language Models (LLMs) and developing sophisticated Agentic AI systems to solve complex business problems.
Platform Expertise: Leverage and integrate core generative AI platforms, including Gemini and Amazon Bedrock, to build scalable and efficient solutions.
MLOps & Tools: Implement MLOps best practices, utilizing tools like MLFlow for experiment tracking, model versioning, and pipeline orchestration.
Quality Assurance: Develop and execute comprehensive testing strategies for LLM applications, including utilizing frameworks like DeepEval for prompt engineering and model output quality.
Analytical Skill: Apply strong analytical skills to evaluate model performance, diagnose issues, and iterate on solutions to achieve maximum business impact.
Collaboration: Work closely with cross-functional teams (data scientists, product managers, and software engineers) to define requirements and deliver integrated AI features.
Required Qualifications:
·
Experience: 4-7 years of professional experience in Machine Learning Engineering, AI Development, or a closely related field.
·
Education: Master’s degree in Computer Science, Data Science, Engineering, or a quantitative field.
Technical Proficiency:
·
Expertise in Python and core ML/Data Science libraries (e.g., PyTorch, TensorFlow, Scikit-learn)
·
Proven experience in deploying models on major cloud platforms (GCP, AWS, or Azure).
·
Deep understanding of the architecture and fine-tuning of Large Language Models
·
Domain Knowledge: Practical experience with MLOps tools (e.g., MLFlow) and validation frameworks (e.g., DeepEval).
·
Problem Solving: Demonstrated ability to apply analytical skills to complex, ambiguous problems and translate insights into actionable engineering solutions.
Preferred Qualifications:
·
Hands-on experience developing applications or services using Google's Gemini API or models.
·
Direct experience with AWS services related to AI/ML, particularly Amazon Bedrock.
·
Experience in building and managing multi-step, reasoning-based Agentic AI systems.
·
Prior experience in optimizing models for latency and cost efficiency in a production environment.
Equal Opportunity Employer
We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.