Highlights:

Role: Senior ML-Engineer

Location: Georgia, Remote

Language: Russian-speaking team; Strong English required (B2)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to strengthen our ML team. We operate as an internal service and centre of excellence for 10+ product teams at Fundraise Up. This means you won't be tied to a single feature: one day you might be optimising donation amounts and upsell offers, and the next you could be building a smart assistant for the admin panel or working on transaction classification.

We actively use not only classical ML, but also RL, and we're expanding our LLM-based solutions — prompt engineering and pipeline design with LLM APIs (OpenAI and equivalents). That's why we're looking for someone with a broad mindset who isn't afraid to experiment and can choose the most effective approach for each task.

The project's main audience and business team are based in the US. Although the product development team is Russian-speaking, you may occasionally need to write in English.

What You’ll Do

• Develop and deploy ML solutions across different business areas using tabular data (uplift models, recommender systems). We are also actively developing projects that will involve e-commerce mechanics.
• Select the most appropriate ML/LLM approaches or propose alternative solutions.
• Build end-to-end ML solutions: data preparation, training, API development, and monitoring.
• Design prompts and LLM API-based pipelines for specific product tasks: classification, content generation, and response quality evaluation.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting); NLP knowledge is a plus
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (CR, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach to development; we value clean code, knowledge of design patterns, and solid engineering practices
• Data skills: advanced SQL; ability to independently and efficiently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking tools and understanding of production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down problems, choose the right tech stack (or justify a non-ML solution), and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Georgia, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to own a high-impact client intelligence initiative. Following a successful proof-of-concept with an external consultant, we are bringing this project fully in-house. The ultimate goal is to generate a comprehensive, enriched list of all potential clients globally — understanding their product requirements, industry verticals, and overall revenue potential — and deploy a scoring model that feeds directly into our sales pipeline.

This is an end-to-end ownership role. You will build from the ground up: data collection, enrichment, modeling, and production deployment. The project is co-managed by company executives and has a high strategic value.

What You’ll Do

• Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data.
• Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators.
• Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects.
• Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook.
• Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis.
• Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly.
• Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way.
• Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.

Challenges You'll Navigate

• At the scale of ~1 million domains, expect domain duplicates, inconsistent data, and significant noise. You'll need to develop robust, cost-efficient filtering pipelines.
• A single model won't cover everything — you'll likely build several targeted sub-models tailored to specific verticals and geographies as the project matures.
• All of this needs to be accomplished without incurring high infrastructure or data costs. Pragmatic, scrappy solutions are valued here.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting) and understanding of modern NLP/LLM approaches
• Proven experience with large-scale web scraping and data pipeline construction
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach; we value clean code, knowledge of design patterns, and solid engineering practices
• Advanced SQL; ability to independently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking and production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down ambiguous problems, choose the right tech stack, and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Infra: linux server admin, distributed computation

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• 31 days off
• 100% paid telemedicine plan
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace.
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Project

As an Associate AI Engineer, you will join the team building internal LLM projects, ranging from client-facing demos to cutting-edge R&D initiatives. These projects will give you hands-on experience and prepare you to contribute to commercial client engagements.

What You’ll Do

• Build LLM and Agentic applications
• Brainstorm ideas for those projects and their implementation
• Take part in the full cycle: from ideation and brainstorming, through implementation, to testing and evaluation of the solutions
• You will have the opportunity to learn and develop your skills by working together with other AI Engineers (ranging from Associate to Lead)
• Participate in research of cutting-edge technologies and products

What You Bring

• Strong fundamentals in software development and problem-solving (Python preferred)
• Experience working in a Scrum team and writing production code
• Experience in using AI and Agentic tools for coding
• Knowledge of SDLC process
• Bachelor’s degree in STEM (or equivalent hands-on experience or bootcamp) as minimum (master's or PhD degree a plus)
• DevOps/MLOps experience including Docker
• Business-oriented, results-driven mindset
• Strong communication skills
• Curiosity and willingness to learn AI/LLM technologies

Nice to have

• Familiarity with cloud infrastructure (AWS/GCP/Azure)
• Knowledge of LLM Python packages: LangChain, LangGraph, LangFuse, vector DBs
• Knowledge of ML Python packages: PyTorch, scikit-learn
• NLP and language modelling knowledge
• Research interest and experience
• Good grasp of mathematics and statistics, including:
• Linear algebra, probability, and basic calculus
• Statistical testing and basic modeling techniques

English level

Upper-intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Project

As an Associate AI Engineer, you will join the team building internal LLM projects, ranging from client-facing demos to cutting-edge R&D initiatives. These projects will give you hands-on experience and prepare you to contribute to commercial client engagements.

What You’ll Do

• Build LLM and Agentic applications
• Brainstorm ideas for those projects and their implementation
• Take part in the full cycle: from ideation and brainstorming, through implementation, to testing and evaluation of the solutions
• You will have the opportunity to learn and develop your skills by working together with other AI Engineers (ranging from Associate to Lead)
• Participate in research of cutting-edge technologies and products

What You Bring

• Strong fundamentals in software development and problem-solving (Python preferred)
• Experience working in a Scrum team and writing production code
• Experience in using AI and Agentic tools for coding
• Knowledge of SDLC process
• Bachelor’s degree in STEM (or equivalent hands-on experience or bootcamp) as minimum (master's or PhD degree a plus)
• DevOps/MLOps experience including Docker
• Business-oriented, results-driven mindset
• Strong communication skills
• Curiosity and willingness to learn AI/LLM technologies

Nice to have

• Familiarity with cloud infrastructure (AWS/GCP/Azure)
• Knowledge of LLM Python packages: LangChain, LangGraph, LangFuse, vector DBs
• Knowledge of ML Python packages: PyTorch, scikit-learn
• NLP and language modelling knowledge
• Research interest and experience
• Good grasp of mathematics and statistics, including:
• Linear algebra, probability, and basic calculus
• Statistical testing and basic modeling techniques

English level

Upper-intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Role Overview

We are looking for a Sr. DevOps Engineer to help build, operate, and continuously improve the secure cloud platforms that power Juvare’s mission-critical enterprise resilience solutions. In this role, you’ll partner across Engineering and Security to deliver reliable, scalable SaaS environments for commercial and federal customers, with a proven track record operating in regulated settings. Experience supporting AI/MLOps workflows is a plus.

Location

• Atlanta / Remote

Must Have

• Cloud Platforms: Strong hands-on experience with AWS and Azure
• Regulated Environments: Experience operating in FedRAMP High, DoD Impact Level 5 (IL5), or equivalent regulated environments
• Compliance & ConMon: Strong understanding of Authority to Operate (ATO) processes, compliance, and continuous monitoring (ConMon)
• GovCloud: Experience working within AWS GovCloud or secure boundary environments
• Databases: Operational experience with managed databases (backup/restore, replication, performance, and access management; Azure SQL and Aurora PostgreSQL preferred)
• Infrastructure as Code: Experience with infrastructure as code (Terraform)
• CI/CD Pipelines: CI/CD pipeline experience (GitLab, GitHub)
• Automation (AI-Enabled): Experience building workflow automation and developer automation using tools like n8n, Replit, or similar
• Containers & Orchestration: Strong experience with containers and orchestration (Docker, Kubernetes, AKS, EKS, ECS/Fargate)
• Monitoring & Observability: Experience with monitoring and observability (Datadog, CloudWatch)
• Security Tooling: Exposure to security tooling (WAF, SIEM, vulnerability management)
• Scripting: Strong scripting skills (Python, Bash, Powershell)
• Production Operations: Experience in production operations (incident response, on-call, RCA)
• Architecture: Strong understanding of networking, security, and system architecture
• AI / MLOps:
  • MLOps Pipelines: Experience with MLOps pipelines (training, deployment, monitoring)
  • Tools: Familiarity with tools like SageMaker, MLflow, Kubeflow, or similar
  • Model Deployment: Experience deploying models to production (real-time or batch)
  • Data & Lifecycle: Understanding of data pipelines and model lifecycle management

Nice to Have

• Experience with LLMs / GenAI workflows (RAG, prompt engineering, fine-tuning)
• Familiarity with vector databases (Pinecone, Weaviate, OpenSearch)
• Exposure to AIOps or AI-driven automation
• Experience with data platforms (Databricks, Snowflake, Redshift)
• GCP experience a plus; comfort operating with a cloud-agnostic mindset
• Multi-cloud or hybrid architecture experience
• Cost optimization and performance tuning
• Jira / Confluence experience

What We're Looking For

• Ownership Mindset: Strong sense of ownership in regulated, high-stakes environments — you treat the platform like it's yours
• Compliance + Speed: Ability to balance compliance, security, and delivery speed without sacrificing one for the other
• Cross-Team Collaboration: Comfortable working across SysOps, Engineering, and Security teams — you're a bridge, not a silo

Additional Information:

This position requires access to information that is controlled by the Export Administration Regulations (“EAR”).  A candidate must qualify as a “U.S. Person” or be otherwise eligible to access EAR covered materials through an EAR exception or license.  A "U.S. Person" as defined by the EAR includes a U.S. Citizen, U.S. national, lawful permanent resident, refugee, or asylee.

As the Company is a partner with the United States government, this position may require access to sensitive government information. Accordingly, candidates must be capable of passing an SF-85 background check and obtaining public trust clearance if required.

Why Join Exadel

We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks.

From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next.

What powers it all? Our people are ambitious, collaborative, and constantly evolving.

About the Project

As an Associate AI Engineer, you will join the team building internal LLM projects, ranging from client-facing demos to cutting-edge R&D initiatives. These projects will give you hands-on experience and prepare you to contribute to commercial client engagements.

What You’ll Do

• Build LLM and Agentic applications
• Brainstorm ideas for those projects and their implementation
• Take part in the full cycle: from ideation and brainstorming, through implementation, to testing and evaluation of the solutions
• You will have the opportunity to learn and develop your skills by working together with other AI Engineers (ranging from Associate to Lead)
• Participate in research of cutting-edge technologies and products

What You Bring

• Strong fundamentals in software development and problem-solving (Python preferred)
• Experience working in a Scrum team and writing production code
• Experience in using AI and Agentic tools for coding
• Knowledge of SDLC process
• Bachelor’s degree in STEM (or equivalent hands-on experience or bootcamp) as minimum (master's or PhD degree a plus)
• DevOps/MLOps experience including Docker
• Business-oriented, results-driven mindset
• Strong communication skills
• Curiosity and willingness to learn AI/LLM technologies

Nice to have

• Familiarity with cloud infrastructure (AWS/GCP/Azure)
• Knowledge of LLM Python packages: LangChain, LangGraph, LangFuse, vector DBs
• Knowledge of ML Python packages: PyTorch, scikit-learn
• NLP and language modelling knowledge
• Research interest and experience
• Good grasp of mathematics and statistics, including:
• Linear algebra, probability, and basic calculus
• Statistical testing and basic modeling techniques

English level

Upper-intermediate

Legal & Hiring Information

• Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more
• Reasonable accommodations are available to enable individuals with disabilities to perform essential functions
• Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs

Your Benefits at Exadel 

Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details.

• International projects
• In-office, hybrid, or remote flexibility
• Medical healthcare
• Recognition program
• Ongoing learning & reimbursement 
• Well-being program
• Team events & local benefits 
• Sports compensation 
• Referral bonuses 
• Top-tier equipment provision

Exadel Culture

We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

CSQ227R88

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ127R310

Candidates located anywhere within the Central or Eastern Time Zones are also eligible for consideration for this role.

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ127R318

As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of  professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps 
• Design and deployment of performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
• Travel to customers 20% of the time
• Databricks Certification

CSQ227R87

Candidates located anywhere within the Central or Eastern Time Zones are also eligible for consideration for this role.

As a Resident Solutions Architect) in our Professional Services team you will work with clients on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.

The impact you will have:

• You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
• Work with engagement managers to scope variety of professional services work with input from the customer
• Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
• Consult on architecture and design; bootstrap hands-on projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.

What we look for:

• 6+ years experience in data engineering, data platforms & analytics
• Comfortable writing code in either Python or Scala
• Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
• Deep experience with distributed computing with Apache Spark™ and knowledge of Apache Spark™ runtime internals
• Familiarity with CI/CD for production deployments
• Working knowledge of MLOps
• Capable of design and deployment of highly performant end-to-end data architectures
• Experience with technical project delivery - managing scope and timelines.
• Documentation and white-boarding skills.
• Experience working with clients and managing conflicts.
• Experience in building scalable streaming and batch solutions using cloud-native components
• Travel to customers up to 20% of the time
• Nice to have: Databricks Certification

Description Summary:    

M3 (www.m3as.com) is a leading provider of hospitality-specific software solutions, delivering cloud-based tools for hotel accounting, financial reporting, labor management, payroll, and business intelligence. Built by hoteliers for hoteliers, M3 empowers hotel owners, operators, and management companies to streamline back-office operations, reduce costs, gain real-time insights, and drive portfolio performance across thousands of properties in North America and beyond.     

M3 is embedding AI into its core product workflows to deliver intelligent automation and insights for the hospitality industry. We operate in a cloud-native environment, and AI solutions are expected to integrate seamlessly with modern application and platform architectures. The Senior ML / AI Engineer is responsible for designing, building, deploying, and maintaining production-grade AI and machine learning solutions, including predictive models, intelligent automation, and emerging LLM-enabled capabilities.

This role partners closely with internal engineering teams and external AI partners to establish scalable MLOps practices, ensure reliable model performance, and build internal AI/ML engineering capability. The position requires both strong applied AI/ML expertise and production engineering discipline. 

Essential Duties:

The duties listed below are the essential functions of this position, and they may change as the needs of the company demand. All associates are expected to do what is necessary to get the work done and to cooperate fully with their supervisor’s requests for additional or altered duties. 

• Design, build, and deploy machine learning models into production environments, including REST API-based inference services and batch or real-time scoring pipelines. 
• Develop scalable training and inference pipelines using structured enterprise data. 
• Establish and maintain MLOps practices including model versioning, monitoring, alerting, retraining workflows, and auditable model lifecycle management. 
• Collaborate with Data Engineering to ensure AI-ready data structures and pipelines. 
• Integrate ML outputs into product workflows in partnership with application engineering teams. 
• Evaluate and prototype new AI use cases aligned to product strategy, selecting the appropriate approach (e.g., supervised learning, embeddings-based similarity, retrieval-driven architectures, or hybrid methods) based on problem context and data characteristics. 
• Work alongside external AI partners initially and progressively transition ownership internally. 
• Define performance benchmarks and ensure production reliability of deployed models. 
• Document processes, best practices, and governance considerations for responsible AI usage. 

Education/Training/Experience:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or related field (or equivalent practical experience). 
• 7+ years of experience in machine learning engineering or applied machine learning roles, with demonstrated experience delivering production-grade AI systems in enterprise environments. 
• Strong programming skills in Python and experience with ML libraries (e.g., scikit-learn, PySpark, pandas). 
• Experience deploying and maintaining ML models in production environments. 
• Experience working in cloud-native environments (Azure preferred; AWS or GCP acceptable). 
• Familiarity with MLOps tools such as MLflow or similar model lifecycle management platforms. 
• Experience working with structured enterprise datasets. 
• Experience evaluating and implementing both traditional machine learning approaches and embedding-based or retrieval-driven architectures (e.g., vector search, similarity matching) is a plus. 
• Demonstrated ability to select the right technical solution for a given business problem rather than defaulting to a single modeling paradigm. 
• Ability to collaborate effectively across engineering, product, and business teams.