Machine Learning Engineer

Overview

Design, build, train and deploy AI models and integrate them into Sitemate's products

Key Responsibilities

• ai integration
• model deployment
• cost optimization
• data pipelines
• experimentation
• documentation

Tasks

-Collaborate with product managers, designers, and engineers to integrate AI into user-facing features. -Deploy, monitor, and continuously improve model performance, accuracy and costs. -Managing cost and latency trade-offs when scaling AI features. -Evaluate and integrate third-party AI services and APIs to accelerate development. -Finding creative solutions for data augmentation when working with limited labeled training data. -Balancing experimentation with reliability: Exploring innovative AI capabilities while still delivering production-ready software that users can trust. -Build and maintain data pipelines to ensure clean, reliable, and scalable training datasets. -Document workflows, share insights, and contribute to best practices in applied machine learning. -Navigating emerging AI technologies: Working with rapidly evolving models, APIs, and frameworks where best practices aren’t always established yet. -Design and ship agentic flows using core product agents and use-case orchestration. -Participate in code reviews and technical discussions, sharing knowledge and shaping engineering standards. -Conduct experiments to evaluate new features, algorithms, architectures, or approaches. -Building in a new domain for the company: Helping define technical foundations, architecture, and standards for AI products in an area where the company doesn’t yet have deep prior experience. -Sitemate builds best in class software products for the built world.

Requirements

• python
• typescript
• aws
• openai
• llms
• 2+ years

What You Bring

-Experience building real-time voice features: speech recognition, conversational flow. -Own full AI generation pipelines: data prep/labeling, model selection and fine-tuning, guarded generation. -Enjoys working with emerging technologies (specifically AI) and thrives in areas where the playbook is still being written. -Built agentic systems (e.g., LangGraph, Bedrock Agents/AgentCore, OpenAI Agents SDK) and/or MCP servers. -AWS cloud experience. -Monitoring/observability: Any ML monitoring tools and observability platform -2+ years shipping production ML/AI features. -Someone who can work independently with minimal ML infrastructure in place. -Access to latest AI tools and platforms. -Enjoys fast-paced work, getting stuff done, and running experiments that have high impact. -Initial projects will focus on intelligent document processing and conversational AI interfaces. -Strong Python for ML and working knowledge of TypeScript. -First ML hire with significant influence on technical direction. -Languages: Python (focus on relevant ML libraries), TypeScript/Node.js. -If you want to focus only on backend or only on frontend work, without touching the full stack. -AI/ML Platforms: OpenAI API, AWS Bedrock. -Experience with model quantization and optimization techniques. -Cares deeply about creating best-in-class user experiences, not just backend logic. -Data privacy & security for AI workloads (PII handling, auditability, least-privilege IAM). -Someone who’s uncomfortable with ambiguity, rapid iteration, or shaping new product directions from the ground up. -Hands-on experience with structured data extraction from unstructured sources. -Comfortable being the go-to ML expert and educating the broader engineering team. -Modern CI/CD: Github actions, AWS CDK. -Knowledge of prompt chaining and few-shot learning techniques. -Experience with vector databases and RAG implementation. -Understanding of ML fundamentals (training/validation/test splits, overfitting, metrics like precision/recall). -Version Control: Git, experience with LFS for large files. -Experience with LLMs (fine-tuning, prompt engineering, evaluation).

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Benefits

-You will have visibility into the standardised career development plan for your role, and access to a professional learning and development budget. -You will get equity options and ownership in Sitemate on a standard vesting schedule. See here for a general overview of how this works. -Direct mentorship from engineering leadership. -You will be remunerated based on your performance. If you are performing well, you won’t need to wait 3 years or have to find better offers elsewhere to receive an increase to your remuneration. 7 out of the last 10 remuneration increases for Sitemate team members have been made pro-actively by management, without the individual needing to even raise the topic of remuneration. -Budget continuous learning. -Flexible hybrid work arrangements. -You will get additional benefits and support as parents - with paid leave for both primary (min. 16 weeks) and secondary carers (min. 6 weeks) including adoption, as well as support and leave for the tragic circumstances of stillbirth or miscarriage. -Our office has fantastic on-site facilities including a rooftop garden, wellness centre, showers and cycle storage. The transport connections are excellent. Every Monday, the team enjoys a catered lunch together from one of the many nearby options. -You will have 20 days PTO, as well as paid compassionate & bereavement leave, sick & carer’s leave, and the ability to work from anywhere for a few weeks per year. -You will have a high degree of autonomy, as the focus is on outcomes and not hours. If you want to block off a few hours to run a personal errand or block off an hour to pick up the kids from school - no worries. No one will be monitoring your time. -2023 Podcast: Listen to CMO Lance Hodgson’s tips on how to supercharge your career -You will have a core and close team around you, but you will also be exposed to and working directly with multiple departments - engineering, product, design, marketing, sales and customer success. -G2 Crowd -We are constantly working to minimise the number of group meetings - daily check ins are all done asynchronously (in your own time) each morning. But spontaneous 1:1s or small sessions are strongly encouraged! -We are very transparent - monthly Allhands meetings provide the team with direct insight into team updates, customer stories, hiring plans and key metrics (NPS, Revenue, Financial Performance). During this Allhands meeting we also hear one ‘life story’ from one of our team each month - learning about different countries and cultures around the world. -Remuneration (including Super): AUD $115,000 - $200,000 -Opportunity to shape AI strategy. -You will get a laptop and a budget to set up your home office. -We place an extremely high value on your time - you won’t be spending your days wasting time on fighting internal systems, botched together spreadsheet processes or doing data entry. -Sitemate has grown from 5 employees in 2018 to 150+, and we’re moving into the next stage of growth! We have a product that customers are strongly engaged with, and every month we get 1000s of new leads in our core/target regions with 0 cold calling and limited marketing spend (made possible by strong word-of-mouth and organic marketing efforts).

About sitemate

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