Overview
Who you'll be working for
Fin techWhat requirements you'll need to be eligible
A degree in Computer Science, Information Systems, or a related engineering field.
3–5 years of development experience, preferably within financial institutions or investment firms.
Solid foundation in machine learning and natural language processing.
Proficiency in Python and familiarity with ML frameworks like TensorFlow or PyTorch.
Exposure to both commercial and open-source LLMs.
Experience in statistical modeling, time-series analysis, or Bayesian inference.
Hands-on experience with model validation, backtesting, and real-time inference.
Understanding of financial data structures and trading systems is a plus.
Familiarity with cloud platforms (AWS), container orchestration (Kubernetes), and microservices architecture.
Strong problem-solving skills and a proactive learning mindset.
What you'll be doing on the job
Work closely with experienced AI engineers and data experts to build and refine LLM-driven solutions.
Apply predictive modeling and statistical techniques to uncover insights from complex financial datasets.
Support the full lifecycle of NLP model development—from data wrangling to deployment.
Enhance model performance through rigorous testing, tuning, and evaluation.
Contribute to the seamless integration of AI features into enterprise-grade platforms.
Stay ahead of the curve by researching emerging trends in AI and NLP.
Maintain clear documentation to support collaboration and scalability.