- Company Name
- Impala Search
- Job Title
- Senior AI/ML Engineer
- Job Description
-
**Job title**
Senior AI/ML Engineer
**Role Summary**
Founding engineer responsible for designing, building, and scaling AI‑driven risk‑and‑compliance systems for fintech and financial institutions. Own end‑to‑end modules, from data ingestion to production‑grade LLM workflows, and work directly with customers and leadership to iterate rapidly and shape technology strategy.
**Expactations**
- Immediate ownership of a core AI module and rapid delivery to production.
- Continuous interaction with end users to surface pain points and deliver tangible value.
- High autonomy, low bureaucracy, and direct influence over engineering culture and product direction.
- Ability to scale systems and processes as the organization grows.
**Key Responsibilities**
1. Own and ship end‑to‑end AI modules from prototype to production.
2. Design and implement foundational LLM infrastructure: data pipelines, model training, inference serving, and API integrations.
3. Conduct user research, run feedback sessions, and iterate based on client needs.
4. Collaborate with the CEO, CTO, and fellow founding engineers to establish engineering best practices and governance.
5. Identify and solve scaling challenges for both technical stack and organizational workflow.
6. Contribute to long‑term product roadmap and strategic decision making.
**Required Skills**
- Strong proficiency in Python (TensorFlow, PyTorch, Hugging Face), Node.js, TypeScript, and React.
- Experience building and deploying LLMs, prompt engineering, fine‑tuning, and agentic AI workflows.
- Expertise in AWS Serverless architecture (Lambda, Aurora, S3, DynamoDB, SageMaker).
- Data pipeline design (Spark, Glue, Airflow) and cloud data storage best practices.
- CI/CD, unit/integration testing, and observability for ML/AI production systems.
- Ability to ship quick, iterate, and optimize under tight deadlines.
- Excellent communication, collaboration, and ownership mindset.
**Required Education & Certifications**
- BSc or MSc in Computer Science, Machine Learning, Data Science, or a related field.
- Practical experience in MLOps and cloud‑based AI deployments.
- AWS Certified Solutions Architect or similar cloud certification is a plus.