AI Jobs

Education Requirements:

• BS (or higher) in Computer Science, or a related field.

Experience Requirements:

• 5+ years of production level experience in one of: Python, Go, Rust or similar language.

Responsibilities:

• Build services, products and infrastructure at the intersection of machine learning and distributed systems.

• Lead/contribute to engineering efforts from design to implementation, solving complex technical challenges around scalability, reliability and resiliency.

• Design and build advanced CI/CD infrastructure and pipelines; help teams debug and build projects and workflows

• Mentor early career engineers; provide technical and cultural guidance

Education Requirements:

• BS or MS degree in Computer Science or a related field, or equivalent work experience.

Responsibilities:

• Maintain deployed AI/ML models, ensuring their reliability and performance over time.

• Design and develop AI/ML models and algorithms to drive innovative applications and products.

• Perform data mining, data cleaning, and data preprocessing.

• Conduct experiments and prototype new models to evaluate their performance and potential impact.

• Collaborate with cross-functional teams, including AI scientists, product managers, and software engineers, to understand business needs and develop scalable and efficient AI/ML solutions.

Benefits:

• Competitive salary

• growth potential

Education Requirements:

• Bachelor’s degree in Electrical Engineering, Mechatronics Engineering, or a related field.

Experience Requirements:

• Hands-on experience with robotics and electrical systems in industrial or mining equipment is an asset.

• Experience with robotics, autonomous driving, AI, or collision avoidance systems is an asset.

• Familiarity with mining environments and the associated operational challenges is an asset.

Other Requirements:

• Proficiency in electrical design, system integration, and troubleshooting.

• Strong problem-solving skills, attention to detail, and ability to work both independently and within a team.

• Excellent communication skills for cross-functional collaboration and technical reporting.

Responsibilities:

• Design and develop electrical systems and components for the integration of intelligent collision avoidance and autonomous driving technologies into mining equipment.

• Collaborate with cross-functional teams, including software, mechanical, and systems engineers, to ensure the electrical components meet overall system requirements.

• System Testing & Validation: Develop and implement testing protocols for evaluating the performance and reliability of intelligent collision avoidance and autonomous driving systems in mining equipment.

• Electrical System Integration: Design and integrate electrical components, sensors, cameras, and LiDAR systems into heavy mining machinery to support autonomous operations.

• Field Testing & Troubleshooting: Supervise our technicians in field tests to ensure systems operate safely and effectively in harsh mining environments. Diagnose and resolve electrical issues and optimize system performance.

Experience Requirements:

• 2 - 4 years

Experience Requirements:

• 2 to 4 years of market competitor focused secondary research experience

• Experience of working in the US, Europe, Middle East, LATAM and APAC markets will be highly preferred

• Experience of leveraging publicly available and 3rd party sources such as SEC filings, EDGAR, Crunchbase, Slintel, Factiva etc.

• Must have skills- MS Office (Word, PowerPoint, Excel)

• 1-4 years of experience in business research firms/corporate strategy or Market Intelligence function

Other Requirements:

• Primary research experience is not relevant

Responsibilities:

• Research: ◆ Prepare understanding of the client’s problem statement and device appropriate research approach ◆ Conduct desk and Contify platform driven research on a particular industry/segment/competitors/topic ◆ Structure and analyze intelligence gathered coherently and succinctly to develop actionable insights ◆ Prepare standard/custom reports around industry/ competitor/company/ topical analysis ◆ Work on various team-specific strategic initiatives

• Project Execution/Management: ◆ Engage with senior members of the client and project teams to identify and address project bottlenecks ◆ Conduct quality check of the work of team members ◆ Contribute actively to project and team discussions ◆ Bring continuous process improvement and solution-oriented approach toward work

• Client Communication: ◆ Conduct written (and verbal communication) with clients to update on project progress and resolve queries ◆ Conduct client walkthrough for reports/analysis prepared

• Other: ◆ Liaison with the Contify platform team to report issues/suggest enhancement measures ◆ Contribute towards organization in the form of internal initiatives

Benefits:

• A team of experienced engineers and researchers, who joined us from most recognized companies and institutions.

• Difficult and interesting problems to solve.

• Pilot license subsidy.

• Hybrid work setting.

• Learning & Development budget: visit conferences of your choice.

Education Requirements:

• Master’s or PhD degree in computer science, physics, mathematics or a related technical field.

Responsibilities:

• Ensure that our neural networks perform strongly in all conditions, by combining work on data, model design, and training.

• Ensure that this performance can be guaranteed, through careful design and verification activities, under our ML certification framework developed in collaboration with regulators.

• Leverage transfer learning to massively increase the amount of training and evaluation data available, in particular through the use of simulation.

Experience Requirements:

• Minimum 6 years of development experience, with at least two years as a machine learning engineer.

Responsibilities:

• Lead the translation of advanced research prototypes into scalable, production-grade software.

• Optimize the utilization of machine learning models, implementing techniques such as early stopping and optimization against adversarial attacks.

• Collaborate closely with data scientists to understand research findings and translate them into practical, scalable solutions.

• Design and implement efficient machine learning systems compatible with diverse data types and integrable with technologies like transformers.

• Drive ambitious projects through collaboration with cross-functional teams, ensuring seamless integration of machine learning technologies across our product suite.

Experience Requirements:

• Minimum of 3 years of experience in manual QA or related fields.

• Experience in identifying and documenting bugs, testing web applications, and working with development teams.

Responsibilities:

• Manually test front-end and back-end systems to ensure functionality, performance, and reliability.

• Collaborate daily with the product team and team leader to review, prioritize, and address reported bugs and system issues.

• Identify and document defects, working with developers to ensure timely resolution.

• Perform regression testing to validate that resolved issues remain fixed.

• Contribute to product design reviews by providing input on potential user experience issues or risks.

Experience Requirements:

• Substantial experience (6+ years) in software development, including python ML technologies and backend technologies.

• Proven ability to transform complex research and algorithms into scalable, market-ready solutions.

Responsibilities:

• Lead, grow, mentor, and manage a team of talented software engineers, ensuring the delivery of high-quality features and products.

• Develop and maintain both the back-end and front-end of DeepKeep’s core applications, contributing as a hands-on developer for 50%-70% of your time.

• Translate advanced research prototypes into scalable, production-grade software, optimizing machine learning models for performance and security (e.g., early stopping, adversarial attack defenses).

• Work closely with cross-functional teams including data scientists, product managers, and machine learning engineers to ensure smooth integration of ML technologies.

• Drive technical excellence and innovation, optimizing distributed AWS systems, serverless architectures, and upholding best practices in code quality.

Education Requirements:

• Bachelor's/Master's degree in Computer Science, Engineering, or a related field.(minimum 4 years of degree).

Experience Requirements:

• 2-4 years of professional experience in backend development using Python.

Responsibilities:

• - Design, develop, and maintain scalable and efficient backend systems using Python and related technologies.

• - Collaborate with other developers, product managers, and stakeholders to understand requirements and translate them into technical solutions.

• - Implement and maintain RESTful APIs for seamless integration with frontend applications and third-party services.

• - Optimize application performance and scalability through code refactoring, database optimization, and other best practices.

Benefits:

• Competitive Salary and Equity

• Comprehensive Insurance

• Flexible Time Off

• Paid Parental and Family Leave

Benefits:

• Competitive Salary and Equity

• Comprehensive Insurance

• Flexible Time Off

• Paid Parental and Family Leave

Benefits:

• Competitive Salary and Equity

• Comprehensive Insurance

• Flexible Time Off

• Paid Parental and Family Leave

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• Extensive experience building and deploying Machine Learning models to production

• Experience managing and developing high performing teams of data scientists and ML engineers

Responsibilities:

• Understanding core problems faced by our Payments & Lending team and leading the team to overcome them - this could include understanding user’s solvency, customer segmentation, retention, payment processing and more

• Finding opportunities for model and product improvements in Cleo's extensive datasets of transactions, bank balances, and customer behaviour.

• Impacting Cleo’s bottom line through improving our lending eligibility and decisioning systems

• You’ll be responsible for people management of the data scientists & ML engineers in your squads, coaching and developing them to deliver on the roadmap.

• You’ll build out the headcount plan and will be responsible for all hiring and team development within your area to support our growth.

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• 3-5 years of experience in data science, machine learning engineering, or related roles

Responsibilities:

• Training and fine-tuning models to help customers get more value from our chatbot and app through deeper personalisation, creating a smarter & more engaging experience, recommending the right content and features to make users love Cleo

• Deploying these models into our production environments using our in-house ML platform, which you can read about on our blog: [Let's have an Espresso: MLOps at Cleo](https://web.meetcleo.com/blog/lets-have-an-espresso-mlops-at-cleo).

• Integrating LLMs hosted by OpenAI, Anthropic, GCP, AWS

• Working cross-functionally with backend engineers, data analysts, UX writers, product managers, and others to ship features that improve our users’ financial health

• Driving the adoption of appropriate state-of-the-art techniques for recommendation, message campaign optimisation, and contextual bandits.

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• Experience in industry machine learning roles as a technical leader or principal/staff engineer.

• Excellent knowledge of both Data Science (python, SQL) and production tools

Responsibilities:

• Training and fine-tuning models to help customers get more value from our chatbot and app through deeper personalisation, creating a smarter & more engaging experience

• Deploying these models into our production environments using our in-house ML platform, which you can read about on our blog: [Let's have an Espresso: MLOps at Cleo](https://web.meetcleo.com/blog/lets-have-an-espresso-mlops-at-cleo).

• Integrating our models with LLMs hosted by OpenAI, Anthropic, GCP, AWS

• Working cross-functionally with backend engineers, data analysts, UX writers, product managers, and others to ship features that improve our users’ financial health

• Driving the adoption of appropriate state-of-the-art techniques for recommendation, message campaign optimisation, and contextual bandits.

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Responsibilities:

• People management:

• Technical leadership:

• Delivery ownership:

• Team development:

• Hiring and growth:

Benefits:

• A competitive compensation package (£110,000 + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• industry experience of using React Native / React with TypeScript for a minimum of 2+ years.

Responsibilities:

• Joining a cross-functional product squad with a mix of frontend engineers, designers, UX writers, backend engineers, data analysts and others to develop features that improve our users’ financial health

• Working on our React Native application, building out amazing experiences for our users which bring financial health to life in the unique Cleo tone of voice.

• Writing automated tests alongside your code to give us the confidence to ship it

• Using AB-Tests, feature flags and other tools that let us iterate quickly

• Using data to dig into user journeys, detecting problems and helping to optimise the Cleo experience

Benefits:

• A competitive compensation package (base + equity) with bi-annual reviews, aligned to our quarterly OKR planning cycles

• Work at one of the fastest-growing tech startups, backed by top VC firms, Balderton & EQT Ventures

• A clear progression plan.

• Flexibility

• Work where you work best.

Experience Requirements:

• has at least 5+ years industry experience of using Ruby on Rails.

Responsibilities:

• Staff IC within a cross-functional product squad and collaborating with a mix of engineers, designers, analysts and other disciplines to develop features that enhance our users' financial health.

• Collaborating with other senior peers in your pillar to provide technical insight into upcoming work, and leading the delivery by helping pull everyone together to get it shipped.

• Mentoring colleagues to help them grow as engineers and actively supporting their development.

• Working on our Ruby on Rails monolith, building data models, APIs, and business logic services.

• Delivering your work using agile methodologies and tools like tests, observability, AB-tests, and feature flags.