Machine Learning Solutions Architect, Symbl.ai
Real-time AI for human interactions
Open for applications
Real-time AI for human interactions
21-100 employees
Open for applications
21-100 employees
Company mission
To accelerate the growth of machines ability to understand human conversations better than human.
Role
Who you are
- Possess a minimum of 10 years of experience in machine learning engineering or software architecture roles, with a focus on designing and implementing ML solutions
- Demonstrate expertise in machine learning algorithms, model development, and evaluation techniques, with hands-on experience in building end-to-end ML systems
- Have proficiency in programming languages such as Python and experience with ML frameworks like TensorFlow or PyTorch
- Exhibit strong problem-solving and analytical skills, with the ability to tackle complex technical challenges and drive innovative solutions
- Possess excellent communication and collaboration skills, with the ability to effectively interact with cross-functional teams and stakeholders
- Show a passion for self-driven learning and staying updated on advancements in machine learning technologies, with a keen interest in applying them to Conversational AI and product development initiatives
What the job involves
- As an ML Solutions Architect at Symbl.ai, you will play a key role in designing and implementing machine learning solutions for our Conversation AI platform and our new product, the Nebula LLM
- You will work closely with cross-functional teams to architect scalable and efficient ML systems that address complex business challenges
- Joining Symbl.ai as an ML Solutions Architect offers the opportunity to lead the design and implementation of cutting-edge machine learning solutions that are deployed in production
- You will have the chance to work on exciting projects at the intersection of ML, Deep Learning, NLP, and Conversational AI, driving innovation and delivering impactful solutions to our customers
- Collaborate with product management and engineering teams to understand business requirements and translate them into scalable ML architectures
- Design end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment
- Implement state-of-the-art machine learning algorithms and models to address specific use cases in Conversation AI and Nebula product projects
- Lead technical discussions and provide guidance on best practices for ML system design, ensuring scalability, reliability, and maintainability
- Work closely with data engineers to optimize data pipelines and infrastructure for efficient model training and inference
- Stay updated on the latest advancements in machine learning technologies and incorporate emerging techniques and frameworks into our ML solutions
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
-6% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
Nov 2021
$17m
SERIES A
Dec 2020
$4.7m
EARLY VC
Total funding: $23.7m
Company benefits
- Health & Wellness: We provide the best national Medical, Vision & Dental coverage through Premera Blue Cross & ICICI Lombard to support you and your family’s health, every step of the way
- Retirement 401(k) Plan: Participate in our plan with a 3% contribution from Symbl to help secure your future
- Flexible Work & Lifestyle: Enjoy the flexibility to work remotely and choose your preferred co-working space. We value work-life balance and offer flexible working hours, supporting both your lifestyle and family needs
- Innovative Work Culture: Thrive in a fast-paced culture that encourages out-of-the-box thinking. Gain exposure to diverse roles and unique challenges
- Paid Time off: At Symbl, we believe in the importance of balance. Enjoy generous vacation, personal days, and public holidays to recharge
- Ownership & Autonomy: Engage in full-stack roles with high levels of responsibility and independence
Company HQ
Pike Pine Retail Core, Seattle, WA
Leadership
Toshish Jawale
(Co-Founder & 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
(Co-Founder & 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.
Share this job
View 9 more jobs at Symbl.ai