Head of Machine Learning

Company Description

Our client is a Norwegian–Bangladeshi technology company developing advanced real estate analytics software at the frontier of data science and machine learning. While prior experience in SaaS or PropTech is advantageous, the company's core emphasis is on strong machine learning expertise and the ability to deliver applied AI solutions with real-world impact.

About the Role

This role is a senior, hands-on technical leadership position responsible for owning the machine learning program end to end—from data strategy and model development through evaluation, backend integration, productionization, and scaling in real-world systems. The focus is on building robust, reliable ML capabilities that are deeply embedded in the companys core technology stack and deliver measurable impact at scale.

Beyond individual execution, this role leads and grows a multidisciplinary team of ML engineers, backend engineers, and MLOps specialists. It sets the technical direction for machine learning across the organization, establishes best practices and standards, and works in close partnership with product and backend engineering to ship high-quality, production-ready systems with clear outcomes and long-term scalability.

Key Responsibilities

• Build, lead, and mentor a high-performing machine learning organization, including hiring, coaching, and career development.
• Define and own the machine learning roadmap aligned with product strategy and business outcomes.
• Establish and enforce best practices for experimentation, governance, documentation, and model lifecycle management.
• Architect, optimize, and review models for tabular data, including feature engineering, interpretability, and evaluation.
• Lay the technical foundation for computer vision and LLM initiatives, including data pipelines, labeling, baselines, evaluation, and serving.
• Drive robust offline and online evaluation frameworks, including experimentation and A/B testing.
• Apply hands-on expertise in large-scale data processing and workflow orchestration.
• Own production ML systems end to end, covering data ingestion, training, deployment, monitoring, and iteration.
• Design and review backend APIs and services that integrate ML into core product flows with strong performance and reliability.
  
• Build and maintain CI/CD pipelines for models and services, including versioning, rollout strategies, and rollback mechanisms.
  
• Operate and scale ML platforms in cloud-native environments with a focus on observability, reliability, security, and cost efficiency.
  
• Partner with product, design, data engineering, and backend teams to translate business needs into measurable ML outcomes.
  
• Communicate priorities, trade-offs, risks, and timelines clearly to executives and key stakeholders.

Skill & Qualifications

• 8+ years of experience in ML/AI/DS or ML engineering, including 3+ years leading teams or technical programs.
  
• Deep expertise in tabular machine learning, including feature engineering, modeling, calibration, and interpretability.
  
• Strong backend engineering skills, including API and service design (REST/gRPC), microservices, and production systems.
  
• Proficiency with Python and modern backend frameworks (FastAPI, Flask, Django) and/or Node.js.
  
• Experience with relational and NoSQL datastores, caching, messaging, and task queues (e.g., PostgreSQL, Redis, Kafka/RabbitMQ, Celery).
  
• Solid understanding of testing, code quality, security, and production best practices.
  
• Strong MLOps experience across model versioning, feature stores, reproducible training, CI/CD, containerization, orchestration, and monitoring.
  
• Hands-on proficiency with Python, PyTorch, and FastAPI
  
• Proven track record of delivering and operating ML systems in production at meaningful scale.
  
• Experience with distributed training or big data tools (e.g., Spark, Ray, Dask).
  
• Familiarity with LLMs, embeddings, retrieval systems, or multimodal pipelines.
  
• Experience building ML systems for SaaS, enterprise, or B2B product environments.
  

Employment Structure

• Hybrid (expected to work 3x a week from office) | Full-time
• Salary: BDT 350,000 – 450,000
• Benefits: 2 Festival bonuses + Comprehensive health insurance covering the employee, spouse, children, and parents
• Work Week: Sunday-Thursday, 9:00 am - 5:00 pm (remote on Sunday's and Thursday's)

Hiring Process

1. Screening interview with Talvette
2. One to two technical assessments
3. One to two interview rounds
4. Receive an offer
5. Join their team full-time