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AlertMedia is a leading risk intelligence and response platform trusted by over 4,000 clients globally to protect people, operations, and brand assets. The company is a high-growth, PE-backed SaaS business with a 7+ year history of AI innovation and a customer NPS of 70+.
You will join as a Senior AI/ML Engineer to lead the evaluation, training, and integration of advanced AI and machine learning models across AlertMedia's product suite. This is a hands-on role where you'll shape the company's AI strategy by identifying appropriate models for use cases, optimizing performance through fine-tuning and prompt engineering, and ensuring responsible deployment.
Key responsibilities include:
- Train and fine-tune supervised learning models (classification, ranking, embeddings) for internal tools and customer-facing features
- Lead prompt engineering and testing efforts to optimize LLM behavior for specific use cases
- Design and implement evaluation pipelines for both LLMs and traditional ML models
- Work with and optimize Elasticsearch-backed data systems powering AI pipelines
- Develop tools and frameworks for prompt iteration, model benchmarking, and performance tracking
- Evaluate and compare commercial and open-source LLMs (OpenAI, Anthropic, Mistral, Meta, etc.) for performance, cost, alignment, and reliability
- Collaborate with product and engineering teams to integrate AI features safely, scalably, and maintainably
- Monitor and continuously improve production AI/ML model performance
- Coordinate with security teams on AI compliance standards
- Stay informed of emerging research in NLP, machine learning, and AI infrastructure
- Proactively identify opportunities to improve AI models, data pipelines, and engineering workflows
You are an applied AI and machine learning engineer with strong data science fundamentals, deeply curious about large language models and practical ML applications. You thrive in fast-moving environments and are comfortable with model training, fine-tuning, prompt crafting, and output evaluation. You balance strong ML fundamentals with pragmatism in selecting the right solution for each problem.
Requirements:
- Bachelor's degree in a technical field (computer science, computer engineering, or related field) preferred
- 5+ years of software engineering experience; Python preferred
- Strong background in applied machine learning and data science
- Experience with LLM evaluation, fine-tuning, and prompt engineering
- Familiarity with ML model evaluation and benchmarking
- Experience with Elasticsearch or similar search/indexing systems is a plus
- Understanding of ML fundamentals and ability to apply pragmatic solutions
- Collaborative mindset and ability to work effectively in cross-functional teams
