Machine Learning Engineer
SweedSalary not specified
Full Time
Mid-level (3 to 4 years)
Not SpecifiedCompensation
Mid-level (3 to 4 years)Experience Level
Full TimeJob Type
UnknownVisa
InsurtechIndustries
Requirements
- Minimum 3 years of backend or fullstack software engineering experience with at least 1 year building production AI, LLM or chatbot systems using Python or TypeScript
- Previous experience using OpenAI, Anthropic or Google Gemini APIs for model inference and fine-tuning
- Experience using data stores such as Postgres, BigQuery, Redis, Elasticsearch or MongoDB, vector stores such as Qdrant or pgvector, message queues such as Kafka or Google Pub/Sub in production environments
- Strong communication skills, e.g., ability to explain technical tradeoffs to non-technical stakeholders and document solutions clearly
- Reliable as an individual, owning the work shipped
- Self-motivated and continuously studies new practices and toolings in data engineering
- Curious, self-driven learner who keeps pace with the fast-moving GenAI ecosystem and actively shares knowledge with the team
- Embodies CG values—bold experimentation, purposeful innovation and authentic collaboration across diverse, global teams
- Ability to analyze business problems and frame them for AI, critically evaluating model outputs, questioning assumptions, and identifying potential biases
Responsibilities
- Build, deploy and maintain AI-native services including fine-tuning or orchestrating LLMs to power applications such as multilingual support and claims assistants
- Design and maintain real-time analytics and AI features that surface product metrics to partners, integrating vector and relational data stores and data APIs
- Implement data governance and security measures and ensure compliance with data privacy regulations and best practices
- Develop a cloud-native multivariate experimentation and optimisation platform, feature-flags, traffic allocation, stats engines, supporting billions of events per day
- Implement robust, observable inference pipelines using containerisation and CI/CD so models run efficiently and securely in production
- Collaborate with other teams to translate business problems into AI-backed features, measure impact and iterate rapidly
Skills
Key technologies and capabilities for this role
Questions & Answers
Common questions about this position
What is the salary for this AI Engineer position?
This information is not specified in the job description.
Is this AI Engineer role remote or does it require office work?
This information is not specified in the job description.
What skills and experience are required for the AI Engineer role?
Minimum 3 years of backend or fullstack software engineering experience with at least 1 year building production AI, LLM or chatbot systems using Python or TypeScript is required. Previous experience using OpenAI, Anthropic or Google Gemini APIs for model inference and fine-tuning is needed. Experience with data stores such as Postgres, BigQuery, Redis, Elasticsearch or MongoDB, vector stores, and message queues like Kafka or Google Pub/Sub in production is also required.
What is the company culture like at Cover Genius?
Cover Genius has a diverse team across 20+ countries and many language groups, committed to diverse cultural programs like “CG Gives” which funds development initiatives in global communities. Their people are described as Bold, Authentic, Purposeful and Inspired, and not Perfect, Traditional, Complacent or Cautious.
What makes a strong candidate for this AI Engineer position?
A strong candidate has at least 3 years of backend or fullstack engineering experience, including 1+ year in production AI/LLM/chatbot systems with Python or TypeScript, experience with OpenAI/Anthropic/Google Gemini APIs, and production use of relevant data stores, vector stores, and message queues.
Cover Genius
Embedded insurance solutions for digital platforms
About Cover Genius
Cover Genius specializes in providing embedded insurance solutions for digital platforms around the world. The company collaborates with major digital companies like Booking Holdings and Ryanair, and its services are available on popular e-commerce sites such as Amazon and eBay. Cover Genius simplifies the integration of insurance products into the purchasing process through a single API, making it easier for its partners to offer insurance at the point of sale. This approach allows customers to access tailored insurance options, including travel protection and extended warranties, without any hassle. Unlike many competitors, Cover Genius focuses on embedding insurance directly into the user experience, which enhances customer satisfaction and streamlines the buying process. The goal of Cover Genius is to provide comprehensive and customized insurance solutions that not only meet the needs of end-users but also support the growth of its partners' businesses.
New York City, New YorkHeadquarters
2013Year Founded
$235.4MTotal Funding
SERIES_ECompany Stage
Fintech, Financial ServicesIndustries
501-1,000Employees
Benefits
Flexible working conditions
Employee stock options
Ongoing learning
Paid parental leave
Wellness initiatives
#WFH when you want
Peer bonuses and founder awards program
International working opportunities
GC Gives giveback program, led by the team
Risks
Competition from Smartpay and Chubb in Asia may hinder expansion efforts.
AutoRek and J.P. Morgan Payments partnership could offer competitive advantages to rivals.
Nezasa and Globespan's personalized travel experiences may reduce demand for travel protection.
Differentiation
Cover Genius offers seamless integration through a single API for global platforms.
The company partners with major digital companies like Booking Holdings and Amazon.
Cover Genius provides tailored insurance products, enhancing customer satisfaction and partner growth.
Upsides
Increased demand for embedded insurance in e-commerce boosts Cover Genius's integration opportunities.
Partnership with Adyen enhances payment experiences, leading to higher conversion rates.
$80M Series E funding indicates strong investor confidence and growth potential.
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