Principal Machine Learning Engineer (AI/ML) - Splore
** of Company: What is the Company About?**
Splore, supported by Temasek and Menyala, is a visionary startup dedicated to revolutionizing how individuals access and engage with information. In a digital landscape flooded with data, the emphasis has shifted from acquiring information to swiftly and effectively pinpointing pertinent insights. Utilizing an AI Answer Engine, Splore delivers direct, context-sensitive answers, revolutionizing how information is unearthed and absorbed.
Splore offers businesses the opportunity to unlock the considerable value of their data assets by employing the company's exclusive Knowledge Index. This enables businesses to expedite decision-making processes with a foundation of deeper insights. Simultaneously, consumers benefit from swift, pertinent, and dependable answers, eliminating the frustration of sifting through irrelevant search outcomes.
Engineered by skilled professionals in machine learning, distributed systems, and consumer applications, Splore.com merges web data with proprietary sources to generate customized and diverse information outputs.
Key Responsibilities
The ideal candidate will lead the ML/AI team as a Principal Machine Learning Engineer, overseeing the entire ML lifecycle from feature development to operationalization and deployment. Serve as the primary ML authority for the CEO and Product Managers, steering advancements in core ML capabilities and improving engineering processes for widespread adoption in target markets. Leading a group of 4-6 AI software engineers, the role involves cultivating a culture that encompasses both AI innovation and ML product implementation. Additionally, this position entails fostering the professional growth, guidance, and mentorship of team members.
Role Specifics:
ML System Blueprint and Development: Conceptualize, design, and supervise the implementation of ML systems placing strong emphasis on data pipelines, MLOps for training/inferencing, and measuring service/model efficiency.
AI Research: Remain current with the latest AI evolutions, focus particularly on generative AI, recognize technologies and models suitable for Splore use scenarios, implement stringent experimentation practices, and drive continuous enhancements to ML features.
ML Evaluation and Enhancement: Institute a standardized model-evaluation approach emphasizing business impact, enforce appropriate model training/evaluation methods with relevant metrics justifying business value.
POC Management and Execution: Work closely with Product Management and Sales departments to craft and deploy POC AI solutions, effectively demonstrating and substantiating their influence.
ML Operations and Expansion: Evaluate business requirements to devise and implement appropriate ML training and inferencing frameworks and pipelines, endorse best practices in ML engineering for training/model optimization, and establish mechanisms for assessing and tracking model performance.
Technical Leadership and Supervision: Provide technical direction to AI engineers, ensuring high-quality technical output and continuous advancement. Provide career guidance and advancement prospects for engineers at various levels of seniority.
Desirable Attributes
The ideal candidate should possess the following traits:
- Adaptability: Flourishes in evolving environments, making well-informed choices amidst uncertainties.
- Collaboration Skills: Strong teamwork abilities required to align AI strategies with business and technical needs, necessitating effective communication across engineering, product, business, and client teams.
- Learning Agility: Comfortable in a start-up environment, unafraid of hands-on problem-solving and learning through experimentation to tackle new challenges. Active engagement with the latest ML trends and technologies.
- Technical Proficiency: An Engineering/Mathematics MS/PhD graduate with 15+ years' experience in ML/AI (with 10 years specifically in AI/ML and 5 years in DL/NLP). Proficiency in Python and hands-on experience with TensorFlow and PyTorch. Proficient in MLOps practices, cloud platforms like Azure, AWS, or GCP, database systems, and large-scale microservice architecture.
The position can translate business requirements into technical needs, with expertise encompassing software testing, benchmarking, and continuous integration.
Software Developer
Architect designers
Looking for 2D AutoCAD specialists to prepare detailed architectural and engineering drawings.
Payment: AUD $500–$1,200 per project
Full-time Hackintosh iOS development
Responsibilities:
- Designing, developing, and implementing iOS applications for our Hackintosh platform
- Collaborating with cross-functional teams to define, design, and ship new features
- Troubleshooting application bugs and implementing solutions
- Ensuring the performance, quality, and responsiveness of applications
- Staying up-to-date with the latest industry trends and technologies
- Providing technical support and guidance to users as needed
Requirements:
- Proven work experience as an iOS Developer or similar role
- Proficient in Objective-C, Swift, and Xcode
- Strong understanding of iOS development best practices
- Excellent problem-solving skills
- Ability to work independently and as part of a team
- Strong communication and interpersonal skills
- Knowledge in web, mobile, and software development, engineering & architecture, customer service, and accounting and consulting specialist
If you are passionate about iOS development and eager to work on innovative projects in the Hackintosh space, we'd love to hear from you. Please apply with your resume and portfolio to be considered for this exciting opportunity.
AI and Automation Engineer
We are currently looking for a dynamic and experienced AI and Automation Engineer to join our AI Innovation team. The ideal candidate will be pivotal in creating cutting-edge AI-powered automation solutions aimed at optimizing Client onboarding, operational efficiency, and financial processes. This position requires a robust combination of software engineering expertise, a profound grasp of Generative AI, and hands-on experience in implementing advanced automation flows.
Key Responsibilities:
Customer Support Automation & Chatbots:
Develop and maintain AI customer chatbots and other automation tools to enhance response times and resolution rates for customer support.
Integrate AI models with existing support channels and backend systems.
Generative AI & RAG Implementation:
Design and optimize applications utilizing Generative AI (GenAI) with a focus on deploying robust Retrieval-Augmented Generation (RAG) pipelines for precise, context-aware responses.
Experiment with and integrate various Large Language Models (LLMs) and foundation models.
KYC & Financial Automation:
Implement secure and compliant automation solutions for Know Your Customer (KYC) processes, encompassing data validation, document processing, and risk flagging.
Develop automation flows for payment handling and reconciliation to guarantee the accuracy, security, and integrity of financial transactions.
Software Development:
Create well-documented, efficient code using Python for machine learning models, automation scripts, and system integrations.
Collaborate with cross-functional teams (Product, Data Science, Operations) to define requirements and provide solutions.
Agentic AI & Workflow Management (A Plus):
Utilize or quickly adapt to AI flow software and platforms like Dify, n8n, LangChain, or other Agentic AI frameworks to construct complex, multi-step automation workflows.
Required Qualifications:
Experience: Minimum 3-5 years in software development, AI engineering, or automation-centric roles.
Programming: Proficiency in Python and relevant libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow/PyTorch).
AI/ML: Demonstrated expertise in NLP/NLU and deploying machine learning models, specifically for chatbots and customer service.
GenAI/RAG: Practical experience in implementing Generative AI solutions and constructing RAG architectures.
Domain Knowledge:
Direct involvement in customer support automation and AI customer chatbot development.
Understanding of financial technology processes, particularly KYC procedures and payment handling/reconciliation.
Preferred Qualifications:
Familiarity with AI workflow software such as Dify, n8n, or other frameworks for building Agentic AI systems.
Experience with cloud platforms (AWS, Azure, or GCP) for deploying and scaling AI/ML services.
Proficiency with containerization (Docker, Kubernetes).
Life @ Crypto.com
Fosters a culture of empowerment and creativity, working alongside a talented, ambitious, and supportive team.
Encourages a proactive and transformational work environment that enables employees to devise innovative solutions.
Facilitates internal growth by providing opportunities to develop new skill sets for personal and professional advancement.
Cultivates a collaborative work culture where colleagues support and assist each other.
Aims to engage stakeholders to achieve the goal of widespread cryptocurrency adoption.
Work Perks:
Competitive salary.
Generous annual leave entitlement, including special occasions like birthdays and work anniversaries.
Flexibility in work hours and supports hybrid or remote work setups.
About Crypto.com:
Established in 2016, Crypto.com caters to over 150 million customers and stands as the world's fastest-growing global cryptocurrency platform. With a commitment to security, privacy, and compliance, Crypto.com aims to accelerate cryptocurrency adoption through innovation and empower the next generation of innovators, creators, and entrepreneurs to foster a fairer and more equitable digital ecosystem.
Crypto.com is proud to be an equal opportunities employer, emphasizing diversity and inclusion in its values. We welcome candidates with diverse backgrounds, perspectives, and skills to strengthen our team.
Personal data shared by applicants will be solely used for recruitment purposes. Please note that only shortlisted candidates will be contacted.
Senior Data Engineer (432)
Ubiminds is a people-first company that collaborates with American software product firms to expand their development capabilities by handpicking elite talent from Brazil. They offer a unique mix of staff augmentation and employer-of-record services.
Ubiminds is aiding a rapidly growing technology and data company focused on APIs, developing modern quoting, enrollment, and member-management solutions for the health insurance and employee benefits sector. They are in the process of expanding their engineering team and introducing new ML/AI-powered features across their platform.
Job Responsibilities:
Take the lead in all ML/AI engineering initiatives as the primary dedicated member in this domain.
Develop, deploy, and deliver ML/AI-driven functionalities across various products.
Collaborate closely with Product, Engineering, and Operations to identify lucrative opportunities and transform them into operational systems.
Manage the complete lifecycle of ML solutions including problem definition, prototyping, modeling, deployment, monitoring, and ongoing enhancement.
Set up best practices, tools, and standards for ML/AI development, experimentation, and visibility.
Enhance data pipelines and feature repositories to support robust ML workloads.
Partake in architecture assessments, roadmap planning, and cross-team coordination.
Mentor colleagues on ML/AI concepts and contribute to team growth as the ML/AI practice expands.
Contribute to a top-notch codebase by following TDD, conducting code reviews, and adhering to well-structured engineering practices.
Required Qualifications:
Proven experience in building and launching ML/AI systems in production environments.
Proficiency across the ML lifecycle - from data preparation to deployment and monitoring.
Hands-on familiarity with advanced AI methodologies such as LLMs and traditional ML algorithms.
8–10+ years of experience in software or ML engineering.
Proficient in at least one major ML/AI programming language (Python preferred).
Comfortable collaborating in a diverse engineering environment (team predominantly uses Ruby).
Skilled in building systems from ground zero in ambiguous settings with substantial autonomy.
Strong communication skills and keenness for transparent, positive collaboration.
Desired Skills:
Experience in designing ML feature stores, embedding retrieval systems, or ML observability frameworks.
Knowledge of data-intensive APIs, large-scale data pipelines, or high-throughput backend systems.
Exposure to infrastructure supporting ML workloads like orchestration and experiment tracking.
Previous experience in mentoring engineers or familiarizing stakeholders with ML/AI practices.
Passion for API-centric products and robust engineering regulations.
Team & Workplace Environment:
A collaborative, experienced engineering organization.
Emphasis on continuous improvement with practices like TDD, pair programming, and code reviews.
Strong partnership with Product for exploration, prioritization, and architecture design.
Addressing impactful challenges in data, APIs, and intelligent system design.
High autonomy in work, contemporary engineering methodologies, and a focus on technical excellence.
About Ubiminds:
Our Culture:
Prioritizing people's needs above all else.
Cultivating a culture of continual self-improvement.
Valuing initiative, ownership, and dedication.
Emphasizing teamwork and collective growth.
Delivering exceptional services and surpassing expectations.
Promoting openness, honesty, and transparency at all times.
Perks and Benefits:
Integrated into a product-focused company with full team support in various areas.
Possess your own MacBook as part of a remote-first policy.
Access to tech discussions, events, and an esteemed community of engineers.
Free English lessons with a native speaker to enhance language skills.
Referral incentive for recommending new team members.
Enjoy office amenities like snacks, massages, beverages, and games at the Florianópolis HQ.
Recruitment Process:
Initial chat with a Tech Recruiter about the role and your background.
Completion of a behavior and code assessment as part of the tech evaluation.
Assessment review by Ubiminds' CS Manager.
Interview with the Hiring Manager before receiving an offer.
Completion of a background check throughout the hiring process.