Machine Learning / AI Engineer

Spotio Ai/Ml Engineer

Spotio is a dynamic, fast-growing American start-up with a 10-year tradition of creating the #1 Sales Engagement Platform. Spotio's platform helps field sales teams manage sales activities, increase the productivity of sales representatives and record field sales insights.

We have offices in Dallas, Texas and Gdansk. In Gdansk, there is a development, product and QA team totalling 21 people (50 people in total globally).

There's no corporate vibe or dress code here. Instead, there's a friendly, collaborative atmosphere and small teams. On Tuesdays and Wednesdays, we meet in the office in Gdansk because we want to. On other days, we work remotely because we can.

The team works normal local business hours and we have calls with the Dallas team several times a week, typically only during overlapping working hours of 2:00pm to 5:00pm Polish time. There is also an opportunity for travel to Dallas, however this is not required.

As Spotio's AI/ML Engineer, you will take full ownership of the direction and execution of our machine learning and AI initiatives. You will maintain our existing production models and infrastructure while architecting new ML systems that power intelligent recommendations, predictive scoring, and AI-driven workflows across the entire Spotio platform.

You will own the end-to-end ML lifecycle: feature engineering, model training and evaluation, production deployment, drift monitoring, and retraining operations. You will also work closely with our engineering and product teams to integrate ML outputs into our LLM layer, shape the AI descriptions and recommendations that reps see in the product, and potentially fine-tune large language models as that capability matures.

Spotio's ML platform is already live in production. The initial build (containerized scoring service, gradient boosting models, feature engineering pipelines, batch retraining, drift monitoring) was delivered by an external consulting team that has since rolled off the engagement. You will inherit a well documented, operational system rather than building from scratch. There will be opportunities to work with the consultants during the onboarding process.

Comprehensive onboarding material is in place, covering system architecture, model training procedures, feature pipelines, deployment workflows, and operational runbooks. Your first focus will be absorbing that documentation and taking operational ownership of the existing platform.

This is fundamentally an ML Engineering role with strong MLOps responsibilities. You will spend most of your time owning, evolving and operating production ML systems, not building research prototypes.

Priorities, in order:

1. Operate and maintain the existing production ML platform (scoring service, retraining cycles, monitoring).
2. Evolve the platform: improve model quality, expand feature engineering, create custom models, add new ML capabilities as the data and product mature.
3. Integrate ML outputs into Spotio's LLM-powered AI layer alongside the engineering team.
4. Explore advanced approaches (reinforcement learning, LLM fine-tuning) as the platform matures.

By the end of your first six months, you should have:

• A complete working grasp of Spotio's ML and data pipeline: scoring service, feature pipelines, training workflows, model registry, and deployment process.
• Confidence monitoring all production models and the ability to diagnose and resolve scoring failures or batch issues independently.
• The ability to retrain and promote new model versions through the established quality gates without external help.
• Strong working knowledge of Spotio's underlying data model (customers, activities, data objects, custom fields) and how it flows into ML features.
• An informed point of view on what to improve next, grounded in what you've actually seen in production.

You will report directly to the CTO (based in Dallas). Day-to-day you will collaborate with:

• The Gdansk engineering team (development squads and QA).
• Dallas-based product and engineering leadership.