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Senior ML/AI Engineer (Colombia)
Bpo2b · Hybrid · Active · BambooHR
Job facts
| Field | Value |
|---|---|
| Company | Bpo2b |
| Title | Senior ML/AI Engineer (Colombia) |
| Normalized title | - |
| Department / team | - |
| Location | Colombia |
| Work model | Hybrid / Hybrid |
| Employment type | Other |
| Salary | - |
| Status | active |
| ATS provider | BambooHR |
| Posted / first seen | 2026-04-30 / 2026-05-30 |
| Changed / last seen | 2026-05-30 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Bpo2b. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through BambooHR. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Bpo2b |
| Source | 4684ccf8-d99c-4e8b-a44e-161773c3c83f |
| ATS provider | BambooHR |
Description
As our lead Senior AI Engineer, you'll take full ownership of the AI and ML capabilities that make our product truly intelligent and hyper-personalized. You'll design, build, and deploy the core AI systems from the ground up, spanning on-device inference for responsive mobile experiences and cloud-based models for deeper personalization and real-time insights. Working closely with product, design, mobile (iOS/Android), and backend teammates, you'll translate high-level travel vision into production-grade AI features like intelligent recommendations, context-aware suggestions, adaptive itineraries, and anticipatory travel assistance. Expect to balance rapid prototyping with scalable, reliable, and efficient AI systems that respect privacy, battery life, and real-world travel variability.This is ideal if you enjoy greenfield AI projects, making foundational modeling and integration decisions in ambiguity, and shipping consumer-facing AI where model quality, latency, and user experience directly define the product.
Key Responsibilities
- Lead the architecture, development, training, optimization, and deployment of AI/ML models and pipelines from prototype to production scale.
- Develop cloud-based AI services (leveraging LLMs and multimodal models via APIs like Gemini, OpenAI, or equivalents) for advanced personalization, recommendation engines, natural language understanding of travel queries, and feedback loops.
- Establish and enforce best practices: clean ML code, experiment tracking, MLOps (model versioning, monitoring, A/B testing, drift detection), automated evaluation pipelines, cost-efficient inference, and ethical AI considerations (bias mitigation, privacy).
- Collaborate on feature definition, data requirements, success metrics, and iteration.
- Handle unique challenges in an AI-powered travel app: multimodal data (location, text, images), sparse/seasonal travel datasets, real-time adaptability, offline/online hybrid inference, and seamless integration with mobile clients and backend APIs.
- Mentor future team members as we expand the AI engineering group and help shape our AI culture from the start.
Required Qualifications
- Professional AI/ML engineering experience building and shipping production AI systems for consumer mobile or web apps (personalization, recommendation, or travel-related experience is a plus).
- Deep hands-on experience with on-device ML: Core ML, TensorFlow Lite / LiteRT, ML Kit GenAI APIs, Gemini Nano integration, model optimization (quantization, pruning), and hybrid on-device/cloud architectures.
- Practical experience with cloud AI/LLMs: fine-tuning, prompt engineering, RAG, tool calling, API orchestration, and building feedback/improvement loops for personalization.
- Proven success owning 0-to-1 AI projects or leading major ML initiatives and
comfortable making foundational decisions on model choice, data strategy, and deployment independently.
- Strong product sense: focus on user-centric metrics (engagement, conversion, satisfaction), low-latency inference, privacy-by-design, and robust evaluation in real-world scenarios.
- Excellent collaboration and communication skills and able to discuss AI trade-offs (accuracy vs. speed vs. cost) clearly with non-technical partners and engineers.
Preferred Qualifications
- Experience with travel/mobility domains (geospatial ML, recommendation systems for itineraries/routes, multimodal travel data, real-time context).
- Familiarity with MLOps tools (MLflow, Weights & Biases, Kubeflow equivalents), vector databases, or agentic workflows.
- Exposure to cross-platform AI consistency (iOS/Android alignment) or generative features in consumer apps.
- Open-source contributions, personal AI projects, or a portfolio demonstrating shipped ML models/systems (especially on-device or personalization-focused).
Full job record
| Job ID | 3a3635cf84397753876f97cc6ea7af8fd4ee656d |
| Org ID | 190c7605-23f6-43d2-8896-9a8d5d8ef639 |
| Source ID | 4684ccf8-d99c-4e8b-a44e-161773c3c83f |
| Board ID | 4684ccf8-d99c-4e8b-a44e-161773c3c83f |
| Provider | bamboohr |
| Provider Job Key | 216 |
| Title | Senior ML/AI Engineer (Colombia) |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | — |
| Department | — |
| Team | — |
| Employment Type | Other |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | Colombia |
| Region | — |
| City | — |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://bpo2b.bamboohr.com/careers/216 |
| Apply URL | https://bpo2b.bamboohr.com/careers/216 |
| First Seen At | 2026-05-30 05:47:31Z |
| Last Seen At | 2026-06-06 08:47:02Z |
| Last Checked At | 2026-06-06 08:47:02Z |
| Last Changed At | 2026-05-30 05:47:31Z |
| Inactive At | — |
| Source Posted At | 2026-04-30 00:00:00Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=bamboohr/board=bpo2b/date=2026-06-06/2026-06-06T08-47-00-966Z-b55606b0ca25e57c905698f67a3f57c3cfc4b2d35fb2dda35f42cb23ad215580.json |
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"description": "<p>As our lead Senior AI Engineer, you'll take full ownership of the AI and ML capabilities that make our product truly intelligent and hyper-personalized. You'll design, build, and deploy the core AI systems from the ground up, spanning on-device inference for responsive mobile experiences and cloud-based models for deeper personalization and real-time insights. Working closely with product, design, mobile (iOS/Android), and backend teammates, you'll translate high-level travel vision into production-grade AI features like intelligent recommendations, context-aware suggestions, adaptive itineraries, and anticipatory travel assistance. Expect to balance rapid prototyping with scalable, reliable, and efficient AI systems that respect privacy, battery life, and real-world travel variability.This is ideal if you enjoy greenfield AI projects, making foundational modeling and integration decisions in ambiguity, and shipping consumer-facing AI where model quality, latency, and user experience directly define the product.<br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Key Responsibilities</span><br>- Lead the architecture, development, training, optimization, and deployment of AI/ML models and pipelines from prototype to production scale.<br>- Develop cloud-based AI services (leveraging LLMs and multimodal models via APIs like Gemini, OpenAI, or equivalents) for advanced personalization, recommendation engines, natural language understanding of travel queries, and feedback loops.<br>- Establish and enforce best practices: clean ML code, experiment tracking, MLOps (model versioning, monitoring, A/B testing, drift detection), automated evaluation pipelines, cost-efficient inference, and ethical AI considerations (bias mitigation, privacy).<br>- Collaborate on feature definition, data requirements, success metrics, and iteration.</p>\n<p>- Handle unique challenges in an AI-powered travel app: multimodal data (location, text, images), sparse/seasonal travel datasets, real-time adaptability, offline/online hybrid inference, and seamless integration with mobile clients and backend APIs.<br>- Mentor future team members as we expand the AI engineering group and help shape our AI culture from the start.<br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Required Qualifications</span><br>- Professional AI/ML engineering experience building and shipping production AI systems for consumer mobile or web apps (personalization, recommendation, or travel-related experience is a plus).<br>- Deep hands-on experience with on-device ML: Core ML, TensorFlow Lite / LiteRT, ML Kit GenAI APIs, Gemini Nano integration, model optimization (quantization, pruning), and hybrid on-device/cloud architectures.<br>- Practical experience with cloud AI/LLMs: fine-tuning, prompt engineering, RAG, tool calling, API orchestration, and building feedback/improvement loops for personalization.<br>- Proven success owning 0-to-1 AI projects or leading major ML initiatives and<br>comfortable making foundational decisions on model choice, data strategy, and deployment independently.<br>- Strong product sense: focus on user-centric metrics (engagement, conversion, satisfaction), low-latency inference, privacy-by-design, and robust evaluation in real-world scenarios.<br>- Excellent collaboration and communication skills and able to discuss AI trade-offs (accuracy vs. speed vs. cost) clearly with non-technical partners and engineers.<br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Preferred Qualifications</span><br>- Experience with travel/mobility domains (geospatial ML, recommendation systems for itineraries/routes, multimodal travel data, real-time context).<br>- Familiarity with MLOps tools (MLflow, Weights & Biases, Kubeflow equivalents), vector databases, or agentic workflows.<br>- Exposure to cross-platform AI consistency (iOS/Android alignment) or generative features in consumer apps.<br>- Open-source contributions, personal AI projects, or a portfolio demonstrating shipped ML models/systems (especially on-device or personalization-focused).<br></p>",
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