Lead Machine Learning Engineer
Launch PotatoSalary not specified
Full Time
Senior (5 to 8 years)
Not SpecifiedCompensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
AI, Customer ServiceIndustries
Requirements
- 5+ years of software development experience in ML infra, ML tooling, or products with ML usage
- Preferred experience with the ML ecosystem (e.g. python, pytorch, faiss, elastic search)
- Excellent communication skills and a vivid imagination
- Passion about engineering and team culture
- Love tackling ambiguous technical problems and developing solutions to problems with significant impact
- Independent thinker who likes to own and solve complex problems
- Interested in exploring the nuance and aesthetic of conversations
Responsibilities
- Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields
- Translating the latest research into high-performing systems and models that can be practically applied to enhance user experiences
- Help set the team's strategic direction, cultivating an environment that encourages innovation and professional growth
- Actively engaging in all aspects of development, from ideation and experimentation to implementation and deployment
- Collaborating with various teams and product managers to develop and implement ML based solutions, ensuring performance optimization and alignment with broader business goals
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What is the salary for this Senior Machine Learning Engineer position?
This information is not specified in the job description.
Is this role remote?
Yes, this is a remote position.
What experience and skills are required for this role?
You need 5+ years of software development experience in ML infra, ML tooling, or products with ML usage. Preferred experience with the ML ecosystem such as Python, PyTorch, FAISS, and Elasticsearch is also highlighted.
What is the company culture like at Replicant?
The company emphasizes passion about engineering and team culture, encourages innovation and professional growth, and consists of great technologists and strong go-to-market leaders.
What makes a strong candidate for this position?
Strong candidates have excellent communication skills, a vivid imagination, love tackling ambiguous technical problems, are independent thinkers who own and solve complex problems, and are interested in the nuances of conversations.
Replicant
AI-powered customer service solutions provider
About Replicant
Replicant provides AI-powered customer service solutions designed for businesses with high call volumes, such as restaurants and retail companies. Their platform operates in the cloud and integrates with existing systems like IVR, CCaaS, and CRM, allowing businesses to authenticate callers and resolve issues efficiently. Replicant's pay-as-you-go pricing model enables companies to adjust their customer service capacity based on demand, making it ideal for handling seasonal fluctuations. The platform is available 24/7, which helps eliminate wait times and enhances customer satisfaction. Replicant stands out from competitors by offering seamless integration with various systems and a flexible pricing structure, aiming to improve customer service operations and overall satisfaction for its clients.
San Francisco, CaliforniaHeadquarters
2017Year Founded
$113MTotal Funding
SERIES_BCompany Stage
Consumer Software, Enterprise Software, AI & Machine LearningIndustries
51-200Employees
Risks
Emerging competitors like Observe.AI and Talkdesk are advancing rapidly.
Businesses are developing in-house AI solutions, reducing third-party dependency.
Privacy concerns and regulatory scrutiny around AI voice data are increasing.
Differentiation
Replicant offers seamless integration with IVR, CCaaS, and CRM systems.
The platform provides 24/7 availability, eliminating customer wait times.
Replicant's AI understands complex speech patterns, including slang and humor.
Upsides
Voice AI is increasingly used to enhance customer service experiences.
AI-driven solutions are expanding into industries like healthcare and finance.
Demand for 24/7 customer service solutions is rising globally.
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