
Expertise in Machine Learning Deployment
1 day ago
We seek an experienced machine learning specialist to join our team.
You will work directly with our team based in the USA and be responsible for designing, building, and deploying AI models for financial services applications.
The ideal candidate will have strong programming skills in Python, familiarity with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn, and experience working with large language models.
Additionally, the successful candidate will have a bachelor's or master's degree in computer science, artificial intelligence, or a related field, and proven experience (3+ years) as a machine learning specialist or a similar role.
We offer flexible hours with reporting time around 1:30 a.m. IST, and a competitive salary range.
Key Responsibilities:- Design, build, and deploy AI models for financial services applications.
- Work with large language models to implement solutions for automation, analysis, and decision-making.
- Develop and optimize code in Python for scalable model training and deployment.
- Leverage AI tools, frameworks, and architectures for experimentation and production systems.
- Collaborate with stakeholders to understand requirements and translate them into technical solutions.
- Ensure models meet compliance, accuracy, and performance benchmarks relevant to the financial sector.
- Strong programming skills in Python.
- Machine Learning Frameworks: Familiarity with TensorFlow, PyTorch, Scikit-learn, or similar.
- LLMs: Familiarity with OpenAI, HuggingFace, LangChain, or similar.
- Familiarity with agentic frameworks.
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
- Proven experience (3+ years) as a machine learning specialist or a similar role.
- Excellent communication, documentation, and collaboration skills.
- Strong problem-solving ability, with the capacity to work independently.
- Experience in generative AI applications for finance.
- Understanding of R and statistical modeling.
- Knowledge of MLOps tools for deployment and monitoring.
- Exposure to regulatory and compliance considerations in the financial services domain.
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