Vespio is a Sentiment Analysis tool that enables sales team to close 4x more deals. Our AI listens to your Sales conversations, breaks them down into smaller parts to assess success rate of each section, delivering better visibility and clarity into customer desires. To ensure deals are won and your sales pitch is always close to 100% successful, the AI offers improvement suggestions based on previously won deals and winning formulas.

We are seeking a talented and experienced ML/NLP Engineer to join our team and help us design and develop innovative AI solutions. As an AI Engineer, you will be responsible for building, training, and optimizing machine learning models, designing and implementing algorithms, and collaborating with data scientists and software developers to create scalable and efficient AI solutions.

Note: We do not work with agencies, contractors and external recruiters. Please, do NOT contact us!!!

Key Responsibilities:

Research and develop new machine learning algorithms and models;
Implement and test machine learning models in production environments;
Provide technical guidance and mentorship to junior engineers and data scientists;
Participate in the development and implementation of best practices for machine learning engineering;
Collaborate with data scientists and software engineers to integrate machine learning models into applications;
Work closely with our product team to understand key customer problems and build software that solves those problems;
Continuously monitor and improve the performance of machine learning models;
Stay up-to-date with the latest developments in machine learning and artificial intelligence.

Qualifications

5+ years of experience in developing and implementing machine learning models and algorithms in production environments;
Strong programming skills in Python and experience with machine learning libraries such as TensorFlow, PyTorch, or scikit-learn;
Experience with distributed data processing frameworks such as Spark, Ray, etc;
Experience with Computer Vision, Deep Learning and NLP;
Ability to communicate technical ﬁndings based on complex quantitative analysis in a clear, precise and actionable manner;
Experience with Microsoft Azure;
Knowledge of analysis tools and packages such as NumPy, Pandas and Matplotlib;
Experience with end-to-end ownership of ML features, including productization, continuous; performance monitoring and on-going improvements;
Knowledge of SQL (e.g. Postgres, MySQL) and NoSQL databases (e.g. MongoDB);
Experience working within a distributed organization, with a worldwide presence is a plus;
Experience with multi-threading and replication concepts in cloud applications is a plus;
Experience working with streaming frameworks such as Kafka, Kinesis is a plus;
Experience managing the model lifecycle with tools like SageMaker or MLflow is a plus;
K8S familiarity is a plus.