Machine Learning Engineer, Symbl.ai
Infrastructure and Operations
Conversation intelligence platform for developers
Open for applications
Conversation intelligence platform for developers
21-100 employees
Open for applications
21-100 employees
Company mission
To elevate the quality of human life through every conversation.
Role
Who you are
- Experience: 5 years to 10+ years
- If you are passionate about shaping the future of AI and machine learning infrastructure, we encourage you to apply and be a part of our journey
- Possess a strong background in machine learning, computer science, or a related field
- Have 5+ years of experience in building and deploying machine learning models in production environments
- Demonstrate proficiency in cloud computing platforms such as AWS, GCP, or Azure
- Have experience with containerization technologies like Docker and orchestration tools like Kubernetes
- Exhibit strong problem-solving skills and the ability to troubleshoot complex technical issues
- Possess excellent communication and collaboration skills to work effectively in a remote team environment
What the job involves
- In this role, you will play a pivotal part in our cutting-edge projects that drive AI innovation
- As a Machine Learning Engineer specializing in Infrastructure and Operations, you will play a crucial role in optimizing and scaling our AI systems for maximum performance and reliability
- We leverage a range of technologies, including but not limited to:
- Machine Learning Frameworks
- Cloud Computing Services
- DevOps Tools
- Containerization Technologies
- Distributed Systems
- Monitoring and Logging Solutions
- CI/CD Pipelines
- As a Machine Learning Infrastructure or Ops Engineer at Symbl.ai, you will architect and maintain a robust, scalable infrastructure, deploying and optimizing machine learning models while ensuring data security and compliance
- Architect and maintain robust and scalable machine learning infrastructure
- Collaborate with data scientists and engineers to deploy and monitor machine learning models
- Implement automated workflows for model training, validation, and deployment
- Optimize and fine-tune the performance of machine learning systems
- Ensure data security, privacy, and compliance within the machine learning infrastructure
- Troubleshoot and resolve infrastructure-related issues
- Contribute to the evaluation and adoption of new technologies and tools in the machine learning space
Our take
Data analytics has changed the way businesses operate - what customers buy, how often, what they nearly buy, etc. An individual’s online experience is full of data, telling a business what’s working, what’s not, and how they can change. But what’s much harder is to collate data from, say, a customer service phone call. That’s where Symbl comes in, with its conversation intelligence software.
Symbl boasts a hefty set of features, including topic and ‘sentiment’ recognition, automatic transcription (with identification of multiple speakers in over 30 languages), as well as question and answers analytics and keyword detection. It’s a thoroughly impressive package, with usages like data analysis from customer calls and performance reviews for customer support or sales teams.
Within the realm of human voice analysis, Symbl has impressive capabilities. But conversation intelligence is a market with other big players, like Gong or Chorus.ai. While Symbl’s features are technically more impressive than those of Gong, Symbl falls short on holistic analysis including SMS and email, which can provide a clearer picture. Symbl works well but has tough competitors to differentiate itself from.
Freddie
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 4 rounds)
Nov 2021
$17m
SERIES A
Dec 2020
$4.7m
EARLY VC
Total funding: $23.7m
Company benefits
- 100% covered health coverage for you, and 90% for your love ones
- 100% covered Life & AD&D, and short-term disability coverage for you
- 401(k) with 3% matching
- Continued education and professional development stipend
- WFH and Wellness stipend
- 18 paid holidays
- Unlimited PTO
- Flexible schedule
Company values
- Connect not transact
- Be self-aware
- Obsess over customer value
- Stay curious
- Commit to growth
- Empower each other
- Do not settle for mediocrity
Company HQ
Pike Pine Retail Core, Seattle, WA
Articles
Leadership
Toshish Jawale
(CTO)Previously worked as a Software Engineer at Media Magic Technologies, was Co-founder of TimeNome, Co-Founder & CTO of upa.io, and was a Software Architect at Amdocs.
Surbhi Rathore
(CEO)Former Software Engineer at Nevis Networks, and Software Development Team Lead at Amdocs. They are also currently an Ambassador for Women in AI and a Member of the Forbes Technology Council.
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