Senior Full Stack Machine Learning Engineer

Senior Full Stack Machine Learning Engineer

About Rapid Labs

Rapid Labs is a US based AI startup focused on building production ready, practical machine learning systems that solve real operational problems. We partner with businesses to design and deploy AI solutions that deliver measurable outcomes, not experiments or hype driven prototypes.

Our culture values ownership, engineering excellence, and clear thinking. We work in fast moving, ambiguous environments where strong fundamentals and real world execution matter more than buzzwords.

About the Role

We are hiring a Senior Full Stack Machine Learning Engineer to own the design, development, and operation of production grade machine learning systems. This role is centered on applied and classical machine learning, not LLM only or prompt driven workflows.

You will work close to the problem space, translating messy operational and business challenges into reliable ML systems that run in production. This is a hands on role for engineers who enjoy building, deploying, and improving real systems in the cloud and taking responsibility for outcomes.

What You Will Do

Build and Own End to End ML Systems

• Own the full machine learning lifecycle from raw data to deployed, monitored, and continuously improving models
• Design predictive, prescriptive, and optimization solutions for use cases such as manufacturing operations, predictive maintenance, quality analytics, and supply chain efficiency
• Apply classical ML and statistical methods including time series forecasting, anomaly detection, regression, classification, clustering, probabilistic modeling, and optimization

Engineer Strong Data and Feature Pipelines

• Build reliable ETL and ELT pipelines for batch and near real time ML workloads
• Perform exploratory data analysis to understand data quality, distributions, bias, and signal
• Design feature pipelines and feature stores that keep training and inference consistent
• Integrate data from APIs, databases, and event streams with strong validation, schema control, and observability

Ship and Operate Production ML

• Deploy models as scalable services using APIs, batch jobs, or streaming inference
• Implement monitoring for model performance, drift, data quality, and system health
• Work closely with platform and software teams to deliver secure, reliable, and cost efficient systems
• Help define and enforce MLOps standards including CI CD, versioning, reproducibility, and rollback strategies

Lead Technically and Collaborate Effectively

• Turn ambiguous business problems into clear ML problem statements, success metrics, and delivery plans
• Make sound technical decisions on model selection, evaluation methods, and trade offs
• Communicate results, risks, and limitations clearly to stakeholders using dashboards, visualizations, and documentation
• Mentor junior engineers and raise the bar for ML engineering practices at Rapid Labs

What We Are Looking For

Must Have

• Seven or more years of experience across machine learning engineering, data engineering, and production systems
• At least five years of hands on experience delivering end to end machine learning solutions in production
• Strong depth in classical machine learning and applied statistics beyond generative AI focused work
• Solid understanding of evaluation techniques, validation strategies, bias variance trade offs, and failure modes
• Advanced Python skills for production ML including clean code, testing, packaging, and performance tuning
• Strong SQL skills and experience designing data models for analytics and ML
• Three or more years of cloud experience with GCP preferred and AWS acceptable
• Hands on experience with BigQuery, Cloud Storage, Dataflow or Apache Beam, Airflow or Cloud Composer, and containerized deployments using Docker and Kubernetes or managed equivalents
• Experience operationalizing ML using tools such as MLflow, CI CD pipelines, workflow orchestration, and monitoring systems
• Proven ability to monitor, debug, and improve models after deployment including drift detection and retraining
• Strong problem solving skills with the ability to translate business needs into ML outcomes
• Clear and confident communication skills with both technical and non-technical stakeholders
• Experience working with cross functional teams including engineering, operations, and product

Nice to Have

• Experience in manufacturing, industrial systems, or supply chain domains
• Ownership of a technical roadmap or AI product lifecycle from planning to delivery
• GCP or AI and ML related professional certifications
• Background in consulting or client facing roles
• Some exposure to GenAI or LLMs is welcome when combined with strong classical ML fundamentals, with LLMs used as supporting components rather than the core focus

Salary & Benefits

• Competitive salary and fringe benefits.
• Paid Time off
• Leaves encashment
• EOBI
• Professional Development
• Career Advancement
• Team Building Activities
• Innovative Work Environment
• Work-Life Balance
• Company trips
• Wellness Programs
• Performance based promotion

Location:

Lahore Office, Islamabad Office, or Remote (Flexible)

This role offers flexibility in how you work. Candidates may choose to join our Lahore office, work from our Islamabad office, or operate fully remote, depending on what works best for them.

Office Hours: 05:00 PM to 02:00 AM (Monday to Friday)

Job Type: Full-time

Application Question(s):

• What is your current salary?
• What is your expected salary?
• What is the duration of your notice period in days?
• Do you have 7+ years of experience as a Senior Full Stack Machine Learning Engineer?

Experience:

• Senior Full Stack Machine Learning Engineer: 7 years (Preferred)

Language:

• English fluently (Preferred)

Work Location: In person