--- title: 'ML Engineer - Power at Kpler' canonical: 'https://feeny.ai/job/ml-engineer-power-kpler-paris-djvkp081sx9t' type: 'job' last_seen: '2026-09-25' --- # ML Engineer - Power at Kpler - **Company:** Kpler - **Location:** Paris, France - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-09-23 - **Last confirmed live:** 2026-09-25 - **Apply:** https://jobs.lever.co/kpler/10105b9b-ed9c-4ebe-8f3b-76b18edeccb8 ## Job description At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors. Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success. ## About the Role As a Machine Learning Engineer at Kpler, you will play a key role in developing and deploying predictive models that power our global commodity, energy, and maritime intelligence platforms. Working closely with Data Scientists, Data Engineers, and Product teams, you will bridge the gap between machine learning experimentation and production-grade software delivery. Your work will directly transform complex data flows into real-time, actionable insights that help world-leading trading firms, industrial leaders, and analysts make critical decisions. ## Key Responsibilities - Architect and deploy ML pipelines: Design, build, and maintain production-grade machine learning workflows and microservices for power market forecasting and electricity grid modeling. - Bridge research and engineering: Transition statistical and machine learning prototypes from initial experimentation into scalable, production-ready Python applications. - Manage time-series and event data systems: Design and optimize database schemas in PostgreSQL to handle high-throughput time-series data, event streams, and normalization routines. - Implement robust MLOps practices: Establish automated model training, backtesting, evaluation, tuning, and feature/model versioning standards across deployments. - Drive data engineering quality: Construct clean ingestion and transformation pipelines, ensuring high integrity, validation, and low-latency access across analytical models. - Champion software excellence: Write modular, well-tested Python code, actively participating in peer code reviews, CI/CD automation, and Agile delivery processes. ## Experience & Background ## What you'll need (Must-haves) - Software engineering foundation: Approximately two to five years of experience as a data-focused software engineer. - Python mastery: Significant experience working with large production Python codebases, rather than working exclusively in notebooks. - Domain knowledge: Deep understanding of electricity-grid fundamentals, including generation, transmission, and electricity markets. - Data engineering & databases: Experience in data engineering, including working with PostgreSQL or similar databases, database design, data normalisation, and managing time-series and event data. - DS & ML research rigor: Proven experience in data science and machine learning research, encompassing statistics, hypothesis testing, model training, evaluation, backtesting, tuning, and model selection. - MLOps & versioning: Practical experience in machine learning engineering, specifically including model and feature versioning. - Engineering practices & communication: Confidence working with Git, code reviews, and Agile methodologies, supported by strong written and spoken English. Nice-to-haves - Cloud platforms: Experience deploying ML workloads on AWS or GCP using Docker and Kubernetes. - Workflow orchestration: Familiarity with orchestration tools such as Apache Airflow, Kubeflow, or MLflow. - Streaming technologies: Exposure to real-time streaming architectures (e.g., Apache Kafka). We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us? We make things happen We act decisively and with purpose, going the extra mile. We build
together We foster relationships and develop creative solutions to address market challenges. We are here to help We are accessible and supportive to colleagues and clients with a friendly approach. Our People Pledge Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team. Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer. By applying, I confirm that I have read and accept the Staff Privacy Notice ## About Kpler ## Company Overview - **One-liner**: Kpler is a data and analytics platform providing real-time intelligence on global commodity flows, vessel movements, and physical trade. - **Entity Type**: Private (PE-backed; primarily founder- and employee-owned) - **Headquarters**: Brussels, Belgium - **Founded**: 2014 - **Founders**: Two engineers (names not publicly listed) who started the company in a kitchen ## Core Business - **Primary industry**: Maritime and commodity trade intelligence; data & analytics (classified as Technology, Information and Media) - **Target customers**: B2B — commodity traders, analysts, shipping professionals, energy companies, supply chain operators, and financial institutions across 40+ markets (liquids, gas, dry bulk, freight, power) - **Mission**: "Serve as the definitive intelligence platform for global physical trade, driving real-time decisions" ## Products & Services - **Kpler Platform**: Subscription-based real-time cargo tracking and commodity flow analytics covering 40+ markets, including vessel movements, volumes, product grades, buyers/sellers, and forecasted destinations. - **MarineTraffic**: World's leading ship tracking and maritime intelligence provider, acquired as a Kpler brand. - **Inbox**: Collaborative communication platform designed specifically for the maritime and global supply chain industry. - **Kpler APIs & Data Integrations**: Developer portal for embedding trade-flow and maritime data into applications, plus an Excel Add-In, Cloud DB, and Snowflake-native data solutions. - **Kpler MCP (Beta)**: Model Context Protocol integration that lets large language models translate plain-language requests into precise API calls, returning answers as narrative, charts, or CSV. ## Market Standing - **Valuation**: Not disclosed - **Key Metric**: Total funding of **$201.6M** across funding rounds, most recently a Private Equity round (April 2022) led by Insight Partners and Five Arrows Growth Capital, followed by a secondary market round (June 2026) led by Sixth Street. - **Annual Revenue**: LinkedIn's data provider reports **EUR 6.7M** — this figure appears significantly understated relative to the company's scale (850+ employees, profitable since launch) and should be treated as an unreliable estimate. - **Notable Investors/Partners**: Insight Partners, Five Arrows Growth Capital, Sixth Street - **Growth Signals**: - Headcount grew **+22.1% YoY** (data provider reports 599 employees; company site reports 850+ employees and 69 nationalities) - Acquisitions: **FleetMon** (March 2023) and **COR-e** (September 2022), plus MarineTraffic - **54 active job postings**; job postings up **+116% YoY** - Expanding into power markets with dedicated Data Engineer and ML Engineer roles - Processes **1.3bn+ AIS signals per day** with a global network of agents and experts ## Competitive Advantages - **Proprietary datasets**: 1.3bn+ AIS signals per day and 245k–255k+ tracked assets/experts create a defensible data moat. - **First-mover in LNG**: Revolutionized the LNG market with the first cargo-tracking solution in 2014. - **Profitable from the start**: Remains primarily owned by founders and team members, allowing long-term product focus. - **Global footprint**: Operations in 10+ countries with workforce distributed across 34+ countries, providing on-the-ground intelligence and 24/7 coverage. - **Brand portfolio**: MarineTraffic and FleetMon extend reach across maritime and supply chain segments. ## Strategic Focus - Building a "singular platform for global trade intelligence" that consolidates commodities, freight, and maritime data. - Expanding into **power markets** and adjacent commodity verticals. - Investing in **AI/ML capabilities**, including the MCP beta for LLM-driven data access and ML engineering hires. - Deepening **data integrations** (APIs, Snowflake, Cloud DB, Excel) to embed Kpler data into customer workflows. ## Why Work Here - **Flexibility**: Hybrid, fully remote, or on-site options; employees can work from central office spaces, sponsored co-working hubs, or fully remote. - **Perks**: WFH monthly allowance for electricity and wi-fi, top-of-range office equipment and setup budget, health insurance coverage. - **Leave**: Global maternity, parental, medical, festival, and compassionate leave policies. - **Culture**: 69 nationalities across the company; regular online and on-site social events; described as "globally minded, flexibility-driven, and innovation-fueled." - **Employer rating**: 3.7/5 from 158 reviews on LinkedIn — Work-Life 3.7, Compensation 3.7, Culture 3.2, Career 3.5. - **Salary benchmarks** (from LinkedIn data): Account Manager ~$99,343/yr, Account Executive ~$111,985/yr, Data Engineer ~€60,000/yr. - **Talent pool**: Frequently hires from competitors and adjacent data providers including MarineTraffic, Spire, Wood Mackenzie, S&P Global, Argus Media, and Bloomberg. ## Sources 1. [kpler.com — Careers](https://www.kpler.com/company/careers) 2. [kpler.com — About Us](https://www.kpler.com/company/about-us) 3. [linkedin.com — Kpler](https://www.linkedin.com/company/kpler) 4. [jobs.lever.co — Kpler](https://jobs.lever.co/kpler) 5. [kpler.com — Homepage](https://www.kpler.com/?r=0) ## Other roles at Kpler - [Sales Specialist - Maritime + Risk & Compliance](https://feeny.ai/job/sales-specialist-maritime-risk-compliance-kpler-new-york-m0h9prdv60ys) — New York, NY - [Account Manager - Maritime](https://feeny.ai/job/account-manager-maritime-kpler-new-york-9tb8n50qwft6) — New York, NY - [Account Manager - Maritime - MEA](https://feeny.ai/job/account-manager-maritime-mea-kpler-dubai-x9ag77d04hrw) — Dubai, United Arab Emirates - [Senior Backend Engineer - Cruise](https://feeny.ai/job/senior-backend-engineer-cruise-kpler-united-kingdom-yc3q6yvgnfwy) — United Kingdom - [Account Executive - Banking/Hedge Funds](https://feeny.ai/job/account-executive-banking-hedge-funds-kpler-new-york-t1z493pr48sp) — New York, NY - [Product Designer - Mobile](https://feeny.ai/job/product-designer-mobile-kpler-united-kingdom-dsw8e5f7axgj) — United Kingdom - [Product Designer - Mobile](https://feeny.ai/job/product-designer-mobile-kpler-athens-8ekf6fp1q2jw) — Athens, Greece - [Senior Fullstack Engineer](https://feeny.ai/job/senior-fullstack-engineer-kpler-athens-06xhxw55petm) — Athens, Greece - [Account Executive, Insurance Vertical](https://feeny.ai/job/account-executive-insurance-vertical-kpler-new-york-cbmxz5tygzsa) — New York, NY - [Account Manager – Shanghai, China](https://feeny.ai/job/account-manager-shanghai-china-kpler-shanghai-cb25r0trc4wm) — Shanghai, China