Senior Machine Learning Engineer, Invoca
$160-252k
Salary only applicable to US based candidates + Bonus Potential + Stock Options
More information about location
Conversation analytics software to grow revenue
Job no longer available
Conversation analytics software to grow revenue
201-500 employees
Job no longer available
$160-252k
Salary only applicable to US based candidates + Bonus Potential + Stock Options
More information about location
201-500 employees
Company mission
To enable revenue team to connect paid media investments to business outcomes, improve digital engagement, and convert more leads into sales.
Role
Who you are
- Proven Experience: 5+ years of professional experience in ML Engineering, AI Engineering, or a closely related data science role with a strong engineering focus
- Deep Learning & Python Expertise: Advanced proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). You're comfortable with data and ML libraries (e.g., spaCy, Pandas, Matplotlib) and have hands-on experience implementing and optimizing deep learning architectures (Transformers, LSTMs, CNNs, etc.)
- Production ML Champion: Demonstrated success in building, deploying, and maintaining NLP and deep learning models in production environments
- Strong Foundational Knowledge: A comprehensive understanding of deep learning, NLP, and core machine learning concepts
- LLM Proficiency: Hands-on experience building, training, and optimizing production-ready LLMs and various deep learning architectures
- Pre-training Experience: Proven experience in pre-training Large Language Models, including data preparation, model architecture design, and training procedures
- Fine-tuning Proficiency: Demonstrable experience in fine-tuning, preference training, LLMs and other deep learning models for a variety of downstream tasks. This includes expertise in transfer learning, adjusting model parameters, and implementing customizations to maximize performance
- Model Optimization: Solid track record of optimizing LLMs and deep learning architectures for production environments
- Reinforcement Learning: Solid understanding and hands-on experience of RL techniques with LLMs or unstructured environments is a plus
- Scalable Model Serving: Advanced proficiency with API-driven frameworks for model serving (e.g., Ray/AnyScale, AWS SageMaker/Bedrock, TGI, vLLM), focusing on building, hosting, scaling, and optimizing model performance
- MLOps Fluency: Intermediate proficiency with MLOps tooling (e.g., Kubeflow, MLFlow), LLM Observability, and best practices including CI/CD for ML models, monitoring, and maintenance
- Data Platform Knowledge: Intermediate proficiency with data platforms like Databricks (Unity Catalog, Model Serving, Jobs/Compute, Delta Lake) or similar for data engineering and analytics
- Big Data Awareness: Basic proficiency with big data technologies (e.g., Spark, Hadoop)
- Conversation Intelligence Interest: Basic understanding of conversation intelligence concepts (e.g., speech recognition, speaker diarization, intent classification)
- Educational Foundation: Bachelor's Degree in Computer Science, Engineering, Statistics, or a related field (or equivalent practical experience). An advanced degree (Master's or Ph.D.) is a strong plus
What the job involves
- As a key member of our Data Platform team, you won't just build models; you'll architect the future of how businesses understand and interact with their customers
- Build Advanced ML Solutions: Train, fine-tune, and deploy sophisticated machine learning models in a scalable, API-driven environment, directly influencing product performance and efficiency
- Innovate with Deep Learning: Design and implement cutting-edge modeling, training, and optimization techniques for deep learning architectures, including the latest foundation models
- Bridge Research to Reality: Engineer robust, production-ready pipelines to adapt foundational AI models for specialized, high-impact business applications
- Build for Scale and Reliability: Develop resilient model serving architectures that seamlessly integrate Large Language Models (LLMs) with enterprise systems, ensuring high availability and performance
- Ensure Excellence in Production: Implement comprehensive monitoring and evaluation frameworks to maintain and enhance model quality, reliability, and ethical performance in live environments
- Elevate Our ML Infrastructure: Contribute to the evolution and enhancement of Invoca's state-of-the-art model training infrastructure and data pipelines
- Champion MLOps Best Practices: Develop and maintain sophisticated MLOps and CI/CD pipelines tailored for machine learning artifacts, ensuring rapid and reliable deployment
- Solve Critical Production Challenges: Act as a key troubleshooter for ML systems, diagnosing and resolving complex issues to maintain operational excellence
- Collaborate for Impact: Work in close partnership with our dedicated data platform team to transform research breakthroughs into robust, production-grade systems
- Drive Customer-Centric Solutions: Partner with product and engineering teams to deeply understand customer needs and deliver innovative ML solutions that provide tangible value
- Foster an Inclusive Environment: Actively support and contribute to Invoca’s diversity, equity, and inclusion initiatives
Our take
Invoca is an AI-powered call tracking and conversational analytics platform enabling marketing, sales, customer experience, and eCommerce teams to better understand and immediately act on information consumers share via conversations, revealing exactly which campaigns are performing and delivering high returns on investments.
The company is a market leader in AI-powered conversation intelligence, serving leading consumer brands in considered purchase industries like automotive, telecommunications, healthcare, financial services, and real estate. It has continued to add new new capabilities throughout the years since its 2008 founding, to further help brands drive more efficient marketing, faster revenue growth, and better experiences in an increasingly challenging economy.
More recently, Invoca has expanded its AI-powered revenue exeuction platform with a new no-code integrations for LinkedIn Ads and Reddit Ads, buiulding on existing support from platforms such as Facebook, Instragram, TikTok, Snapchat, and Pinterest. These additions allow marketers to directly connect social ad spend to phone calls, conversations and revenue. As pressure mounts on marketing teams to provide business impact beyond clicks and impressions, this expanded social advertising ecosystem strengthens Invoca's position as a leader in conversation intelligence and performance-driven marketing.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
5% employee growth in 12 months
Company
Funding (last 2 of 7 rounds)
Jun 2022
$83m
SERIES F
Oct 2019
$56m
SERIES E
Total funding: $199.8m
Company benefits
- Flexible Time Off: We encourage a healthy work-life balance. Our flexible paid time off policy allows you to recharge and take time away as needed.
- Healthcare: Invoca offers a health care program that includes medical, dental and vision coverage. There are multiple plan options to choose from so you can make the best choice for yourself, partner and family.
- Mental Well-being & Employee Assistance Program: Invoca offers well-being support on issues ranging from personal matters to everyday life topics through the WorkplaceOptions program.
- Paid Family/Medical Leave - up to six weeks 100% paid leave for baby bonding, adoption, and caring for family members, and up to twelve weeks 100% paid leave for one’s own medical leave
- Invacation (Sabbatical): We thank our long-term team members with a bonus after seven years of service.
- Wellness Subsidy: In further support of your well-being, Invoca provides a wellness subsidy that can be applied to a gym membership, fitness classes and more.
Company HQ
Santa Barbara Downtown, Santa Barbara, CA
Leadership
Gregg Johnson
(CEO)Prior to joining Invoca in 2016, Gregg spent nearly 10 years at Salesforce, while there, he held a number of roles, including VP of Product Management (Chatter) and SVP of Product Management (Marketing Cloud). He also worked as a COnsultant at Boston Consulting Group and as a Sales/Marketing Manager at Ullink.
Peter Isaacson
(CMO)Peter is also an Advisor at Folloze and ClickZ.com as well as a Contributor to Forbes Communication Council and a Member at Revenue Collective. Previously, he was the CMO at Replicant, Demandbase, and Castlight Health. He also spent nearly 14 years at Adobe Systems, working as a Senior Director of Brand Marketing, VP of WW Field Marketing, and VP of WW Education Vertical Business.
Teresa Dietrich
(CTO)Prior to joining Invoca in 2024, Teresa was the Chief Product & Technology/Community Officer at Stack Overflow. She also served as the GLobal Head of Product & Engineering at McKinsey New Ventures and as CTO at Namely.
Michael DiFilippo
(CFO)Prior to joining Inovca in 2019, Michael was the CFO & Chief Administrative Officer at AppDirector. He also served as a VP/Division CFO (SaaS Division) at Citrix.
Ben Sullivan
(CRO)Ben joined Invoca in 2017 as a Senior VP of Sales, moving into the role of Executive VP of Sales in 2021 and CRO in 2025. Prior to Invoca, he spent 8 years at ON24 as a VP of Strategic Alliances & Business Development and VP of Worldwide Sales.
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