Summary
As a Research Engineer at Smarsh, you will be analyzing a wide range of unstructured communications data to address problems for our customers. The Research Engineer is responsible for the development and evaluation of new research ideas including development, support, and improvement of existing capabilities. Smarsh is looking for Research Engineers to help shape the frontiers of multimodal communications research. We are seeking candidates who will excel in fast-paced environments and deliver results with precision and finesse. The ideal candidate will be someone who’s passionate about exploring new technologies, navigating complex and impactful problems, and building high-performance research infrastructures.The role will involve working with the Research Engineering team, collaborate with the Data Science team, and align with the Product Managers in analyzing complex communications data, generating insights, and creating solutions as needed across a variety of tools and platforms. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights across multimodal data sets with a hands-on/can do attitude.The role offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more.How will you contribute?Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunitiesData annotation and quality review Exploratory data analysis and model fail state analysisAttend and actively participate in planning, stand-ups, retros, and other team meetings and discussionsContribute to Research discussions
Time Allotment:70% Machine Learning model development and evaluation20% interaction with stakeholders to understand modeling needs10% Machine Learning model supportWhat will you bring?Required Education and Experience: Bachelor’s degree in Computer Science, Applied Math, Statistics, or a scientific field with research emphasis1+ year research experience working with data & analytics (including school)Experience working with PythonFamiliarity with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, lightning, Nvidia NeMoExperience using Git, Linux/Unix, an IDEs
Preferred Education and Experience:Master’s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field1+ year experience working with NLP, text analytics/classification, audio analyticsKnowledge of transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, and GPT-x etc.)Experience in using various Large Language Models (LLM)Experience with natural language processing toolkits like NLTK, spaCyKnowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and KubernetesCloud computing (AWS, GCS, Azure)$145,000 - $160,000 a year
The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process. 
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training. 
Local cost of living assessments are done for each new hire at the time of offer.