Hire a Dedicated AI / ML Engineer
AI engineers are not data scientists — they are engineers who happen to work with AI. Our dedicated AI engineers build things that go to production: LLM-powered features with structured output and cost monitoring, RAG systems backed by vector stores, classification and extraction models integrated into real business workflows, and AI automation pipelines that handle edge cases and failures gracefully. They work in Python and TypeScript, are fluent in the OpenAI and Anthropic APIs, and have built systems in healthcare, legal, logistics, and e-commerce contexts.
Monthly rate
Part-time
$900 – $1,600/mo
Full-time
$1,800 – $3,200/mo
Western equivalent: ~$12,000/mo
Save up to 73% vs AU/UK/US hire
Why Codalyst Tech
Company-backed — not freelance
You hire through us — a registered company with a clear contract, NDA protection, and an escalation path if anything goes wrong.
Company-backed contract — not a freelancer agreement
Exclusive assignment — not shared across clients
Pre-vetted and interview-approved before you commit
Onboarded within 7 business days
What they do
Responsibilities
What your dedicated AI / ML Engineer will own as part of your team.
- LLM feature integration (OpenAI, Anthropic, Cohere)
- RAG pipeline architecture and implementation (vector stores, chunking, retrieval)
- Prompt engineering and systematic prompt evaluation
- Structured output parsing and validation (Pydantic, Zod)
- AI automation workflow design and implementation
- Token cost monitoring and budget optimisation
- Model evaluation framework design and test suite maintenance
- Fine-tuning data preparation (where applicable)
Expertise
Core skills
Tooling
Tools & platforms
Services this role delivers
Hire for a project instead
Where this role adds value
Industries we serve with this role
A dedicated AI / ML Engineer delivers measurable impact across 9 industries. Click any card to learn how we work within that sector.
E-Commerce
Online retail businesses selling physical or digital products — from single-brand Shopify stores to multi-vendor marketplaces and D2C brands scaling to 7+ figures.
- Cart abandonment rates above 60% with no structured recovery workflow
- Inventory data spread across Shopify, spreadsheets, and warehouse software
Healthcare
Private clinics, specialist practices, allied health providers, telehealth platforms, and health-tech startups — digitising clinical and administrative workflows while navigating data compliance requirements.
- Appointment booking managed through phone and email — high no-show rates
- Patient records in paper or legacy systems that cannot talk to each other
Legal
Law firms, barristers' chambers, legal tech startups, and in-house legal teams — modernising document-heavy, process-intensive operations while meeting strict confidentiality requirements.
- Document review and due diligence consuming billable hours that should not be
- Matter intake and onboarding done through email chains with no tracking
Logistics & Supply Chain
Freight forwarders, 3PLs, courier companies, warehouse operators, and supply chain technology providers — managing complex, time-sensitive operations across multiple locations and partners.
- Shipment status visible internally but not to customers — constant inbound enquiries
- Driver scheduling and route optimisation done manually or in spreadsheets
Education
Private schools, tutoring companies, online course creators, EdTech startups, and vocational training providers — building and scaling digital learning experiences and administrative systems.
- Student enrolment and onboarding managed through email and spreadsheets
- Course content delivered through generic platforms that do not match the brand
Real Estate
Property agencies, property management companies, developers, buyers' agents, and PropTech startups — digitising property listings, lead management, and portfolio administration.
- Lead management spread across email, portal notifications, and sticky notes
- Property listings manually duplicated across portals (REA, Domain, website)
Fitness & Wellness
Gyms, personal trainers, yoga studios, wellness centres, online fitness coaches, and health app startups — managing memberships, bookings, and digital content delivery.
- Class bookings managed through WhatsApp or phone — confirmation chaotic
- Membership billing on manual cycles with high failed payment rates
Restaurants & Hospitality
Independent restaurants, cafe groups, franchise operators, catering companies, and food delivery brands — managing orders, reservations, POS operations, and digital marketing.
- POS system fees per terminal eating into already-thin margins
- Online ordering platform commissions (15–30%) eliminating delivery profitability
Cleaning & Facilities
Residential cleaning companies, commercial cleaning contractors, facilities management firms, and cleaning franchise operators — managing scheduling, staff, quotes, and recurring client relationships.
- Job scheduling done through WhatsApp or phone with frequent miscommunication
- Quote generation manual and slow — losing jobs to faster competitors
Common questions
Everything you need to know before hiring a dedicated AI / ML Engineer.
You hire a specific person — not a rotating pool. We match you with a vetted professional based on your stack, domain, and working style, you conduct a technical interview before committing, and the person is assigned exclusively to your project for the duration of the engagement. They work within your timezone overlap window, join your team's communication tools (Slack, Teams), and participate in your sprint ceremonies. We handle HR, payroll, equipment, and benefits on our side. You direct the work.
Yes — always. We present 1–2 matched candidates with their CV, portfolio, and a summary of why we think they fit your requirements. You interview them before any engagement begins. If the first candidates are not right, we keep searching at no extra cost until you find someone you want to work with.
Within the first 30 days, if the placement is not working — for any reason — we replace them at no extra cost. After the first 30 days, we require 2 weeks notice to transition to a replacement so there is no knowledge gap. Replacement sourcing is included in your engagement at no additional charge.
A data scientist focuses on statistical modelling, experimentation, and deriving insights from data — they live in notebooks and produce research outputs. An AI engineer builds production systems that use AI models — they write production-grade code, integrate LLM APIs, build reliable pipelines, and deploy to real environments. Most businesses building AI-powered products need an AI engineer, not a data scientist.
Pakistan Standard Time (PKT) is UTC+5. This creates a 3–5 hour overlap with UK/EU mornings, a 4–6 hour overlap with Middle East business hours, and an async-friendly relationship with US/Canada (with a 2–4 hour overlap possible with early starts). We set timezone expectations upfront and ensure a minimum 3-hour synchronous overlap per day with your team.
Ready to hire a dedicated AI / ML Engineer?
Tell us your requirements and timezone. We will present matched candidates within 7 business days.