ML Engineer

We offer the industry’s only platform that fuses customer identity and anti-fraud solutions – customer identity management, identity verification, and fraud prevention.

We sell to industries with large, consumer-facing businesses such as: banking, financial services, insurance, fintech, gaming, ecommerce/retail, telco / media, utilities, etc.

About the Opportunity

Transmit Security is a top player in its game and is heading for an exciting year. In this role you will be responsible for research and development of initiatives to advance AI / ML technologies at Transmit. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats and enhance customer experience.

What You'll Be Doing

• Cover a wide range of areas – from leveraging LLMs to enhance customer investigation experience to novel usage of AI for fraud prevention/identity security.
• Leverage predictive models to optimize customer experiences that will affect millions of users worldwide.
• Conduct Ideation and experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments.
• Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.
• Perform data exploration and analysis.

Qualifications

• Bachelor's degree in computer science or a related field from a familiar university
• At least 3 years of experience as a Data-scientist / ML Engineer
• Experience in designing, training, and evaluating models
• Strong knowledge of deep learning models and common model architecture such as transformer models, CNNs, RNNs, and LSTMs.
• Familiarity with cloud-based infrastructure.
• Independent, persistent, and a "getting things done" person.
• Excellent interpersonal skills.

Advantages

• Master’s degree in Computer Science or a related field.
• Knowledge of programming languages that are used in AI research, such as Python, and experience with AI frameworks (e.g., Hugging Face, LangChain, OpenAI, scikit-learn, TensorFlow, PyTorch)
• Experience in software engineering and with data structures
• Expertise in natural language processing, especially practical experience developing modern, transformer-based language models