Securiti has been widely recognized as an industry innovator, being named “Most Innovative Start-up” at RSA Conference 2020, Leader in the IDC Marketplace, Leader in the Forrester Wave Privacy Management Software, and winner of the 2020 HPE-IAPP Innovation Award. The company is being built by proven serial entrepreneurs and executives who have successfully built and scaled high-growth global companies before. We have multiple backend development roles open and if you aspire to work on cutting-edge technologies and frameworks, side by side with some of the smartest technologists, this may be a unique place for you. You will be working as a part of a distributed agile team, building a new SaaS platform that underpins a suite of enterprise applications solving a variety of hard data analytics and enterprise problems.
Responsibilities:
- Work with a team of data scientists on end-to-end productization of generative AI related products and/or applications.
- Devise approaches and pipelines including, but not limited to, data gathering, machine learning, evaluation frameworks.
- Work closely with software teams to integrate ML/DL modules ensuring best practices in design and implementation.
Minimum Qualifications:
- Bachelor's degree in Computer Science or related field along with at least 2 years of experience working on development of core ML/DL applications.
- Highly proficient using core classical machine-learning techniques in data clustering, regression, and classification.
- Successfully applied more advanced classical machine-learning techniques to a real-world problem, such as support vector machines, gradient boosted decision trees, or random forests.
- Proficient using core neural network architectures, including feed-forward, convolutional, and recurrent architectures.
- Experience applying intermediate deep-learning training techniques such as distillation, quantization, contrastive learning, or variational auto-encoding.
- Can describe the operation of advanced neural network designs such as generative adversarial models, or transformers.
- Experience in natural language processing in an academic or industry setting.
- Proficient using Keras (preferred), TensorFlow, or PyTorch.
Preferred Qualifications:
- Master’s degree in Data Science or related field, with applied industry experience.
- Experience with LangChain and related GenAI frameworks.
- Experience using embedding based models in real world applications for a variety of NLP related tasks.
- Experience applying zero-shot, few-shot learning and fine-tuning LLM models for domain specific tasks.
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