machine engineer

Alignerr

<div>
 
 Machine Learning Engineer - AI Data Trainer
 
 
 
 <ul>
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 Location: Remote
 
 
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 </ul>
 
 About The Job
 
 
 
 At Alignerr, we partner with the world&rsquo;s leading AI research teams and labs to build and train cutting-edge AI models.
 
 
 This initiative focuses on recording how an AI reasons and executes actions sequentially to handle practical assignments. Specialists draft precise, organized logs demonstrating strategizing, tool implementation, and choice-making, producing the data required to teach models to solve problems consistently in actual environments.
 
 
 
 Organization
 
 : Alignerr
 
 Position
 
 : Machine Learning Engineer - AI Data Trainer
 
 Type
 
 : Hourly Contract
 
 Compensation
 
 : $50&ndash;$70 /hour
 
 Location
 
 : Remote
 
 Commitment
 
 : 10&ndash;40 hours/week
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Draft precise, organized logical logs for sophisticated technical challenges.
 </li>
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 Record sequential strategizing and choice-making workflows.
 </li>
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 Generate training datasets that illustrate proficient tool interaction for AI models.
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
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 Professional expertise in Machine Learning, Engineering, or a technical discipline.
 </li>
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 Superb skill in explaining intricate logical processes and methodologies clearly.
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 Critical thinking skills to audit and refine AI-generated reasoning steps.
 </li>
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 Master's Degree or PhD
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
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 Prior experience with data annotation, data quality, or evaluation systems.
 </li>
 <li>
 Master's Degree or PhD
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Competitive pay and flexible remote work.
 </li>
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 Collaborate with a team working on cutting-edge AI projects.
 </li>
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 Exposure to advanced LLMs and how they&rsquo;re trained.
 </li>
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 Freelance perks: autonomy, flexibility, and global collaboration.
 </li>
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 Potential for contract extension.
 
 
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 </ul>
 
 Application Process (Takes 15-20 min)
 
 
 
 <ul>
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 Submit your resume
 </li>
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 Complete a short screening
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 Project matching and onboarding
 
 
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 </ul>
 
 PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 
</div>

Machine Learning Engineer

Avenue Code

<div>
 
 Avenue Code is the leading software consultancy focused on delivering end-to-end development solutions for digital transformation across every vertical. We&rsquo;re privately held, profitable, and have been on a solid growth trajectory since day one. We care deeply about our clients, our partners, and our people. We prefer the word &lsquo;partner&rsquo; over &lsquo;vendor&rsquo;, and our investment in professional relationships is a reflection of that philosophy. We pride ourselves on our technical acumen, our collaborative problem-solving ability, and the warm professionalism of our teams.
 
 
 Avenue Code has been believing in and promoting plurality actions for over 10 years, understanding that recognizing differences and fostering a safe environment, employment opportunities, representation, and support are the best ways to promote an increasingly equitable culture.
 
 
 
 
 
 
 
 
 About the opportunity:
 
 <ul>
 <li>
 Experience 10&ndash;15 years in data governance or data stewardship, including 3&ndash;5 years focused on AI/ML data Experience working with enterprise-scale data platforms and large organizations Technical Skills Strong understanding of AI/ML data pipelines: ingestion, labeling, feature engineering, model training Familiarity with MLOps tools such as MLflow, Azure ML, SageMaker, Databricks Experience with data governance/catalog tools (Collibra, Atlan, Alation, Informatica) Working knowledge of SQL and basic Python
 </li>
 <li>
 Experience with cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) Understanding of feature stores, model registries, and data versioning Governance &amp; Compliance Ability to develop and enforce AI data governance policies Knowledge of GDPR, CCPA, and responsible AI guidelines
 </li>
 <li>
 Experience conducting bias reviews, data quality checks, and maintaining data lineage Business &amp; Leadership Skills Strong analytical thinking with the ability to translate insights into recommendations
 </li>
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 Excellent communication skills across executive and technical teams
 </li>
 <li>
 Proven ability to lead cross‑functional governance discussions and drive adoption Experience in process improvement and implementing governance workflows Soft Skills Detail‑oriented, organized, and capable of managing multiple priorities Strong stakeholder‑management and relationship‑building skills Self‑motivated, adaptable, and comfortable working in a rapidly evolving AI environment
 </li>
 </ul>
 
 
 
 
 
 
 
 
 
 
 &ldquo;Avenue Code discloses salary range information based on our commitment to fairness and transparency. We consider a wide range of factors such as internal equity, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, business or organizational needs, and others. At Avenue Code, it is not typical for an individual to be hired at or near the top of the range for their role, and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for a Machine Learning Engineer is from USD 100k to USD 140k per year."
 
 
 
 
 
 
 
 
 Avenue Code reinforces its commitment to privacy and to all the principles guaranteed by the most accurate global data protection laws, such as GDPR, LGPD, CCPA and CPRA. The Candidate data shared with Avenue Code will be kept confidential and will not be transmitted to disinterested third parties, nor will it be used for purposes other than the application for open positions. As a Consultancy company, Avenue Code may share your information with its clients and other Companies from the CompassUol Group to which Avenue Code&rsquo;s consultants are allocated to perform its services.
 
</div>

<div><div>We help the world run better 
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging &ndash; but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.</div><div></div> 
What you&rsquo;ll build 
In this role, you'll build and operationalize machine learning and AI capabilities that from idea to production and deliver measurable product value. You'll develop data move pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks for use cases such as recommendation, forecasting, anomaly detection, classification, NLP, semantic search, and generative AI.
Your work will include feature engineering, experiment design, model tuning, offline and online validation, and integration of models into scalable product architectures. You'll help improve LLM-based workflows, including prompt design, retrieval-augmented generation, vector search, guardrails, and response quality evaluation. You&rsquo;ll also strengthen the engineering backbone around AI through CI/CD, monitoring, observability, testing, and model lifecycle automation so solutions are reliable, cost-aware, secure, and ready for enterprise scale. 
What you bring: 
<ul><li>
You bring strong programming skills in Python, along with working knowledge of Java or Go, for building production-grade services and APIs
</li><li>You have a solid understanding of machine learning fundamentals, including supervised and unsupervised methods such as classification, regression, clustering, ranking, and recommendation systems
</li><li>You have hands-on experience with deep learning frameworks (e.g., PyTorch or TensorFlow) for model training, fine-tuning, and inference
</li><li>You demonstrate strong capabilities in data preparation, feature engineering, data validation, and model evaluation using appropriate offline and online metrics
</li><li>You have experience building, deploying, and integrating ML models into production systems through batch, real-time, or streaming pipelines
</li><li>You are familiar with generative AI concepts, including LLMs, embeddings, vector databases, prompt engineering, and retrieval-augmented generation, and how to apply them in practical use cases
</li><li>You bring working knowledge of MLOps and modern data infrastructure, including experiment tracking, model versioning, CI/CD, and tools such as Spark, Kafka, Airflow, and feature stores
</li><li>You have experience operating ML systems in production, including monitoring for drift, latency, accuracy, cost, bias, and performing debugging and failure analysis to ensure reliability and business impact</li></ul> 
About You 
<ul><li>
You have 1-3+ years of experience in machine learning engineering, software engineering, or a related field, with a track record of deploying models into production
</li><li>You are passionate about building reliable, scalable ML systems and take ownership of delivering end-to-end solutions
</li><li>You balance experimentation with engineering rigor, making thoughtful trade-offs to ensure models are both innovative and production-ready
</li><li>You are a collaborative problem-solver who thrives in ambiguous environments and is motivated by delivering measurable business impact</li></ul> 
Where you belong:<div> 
You will be part of a growing team of AI and industry experts dedicated to serving customers across the Kingdom of Saudi Arabia / United Arab Emirates. We are building a collaborative, high‑impact environment that brings together deep AI expertise, strong industry knowledge, and regional understanding to help customers innovate, transform, and lead in their markets.</div><div>
This team thrives on working together to turn complex business challenges into practical, scalable solutions. You will find an environment that values curiosity, ownership, and continuous learning, where new ideas are encouraged and real‑world impact matters. This is a place for people who enjoy building something new. You will thrive here if you are customer‑centric, motivated by meaningful outcomes, and comfortable navigating ambiguity in a fast‑evolving AI landscape.</div> 
About the team
We are a team of engineers passionate about building valuable, scalable AI frameworks that drive real business impact. We thrive on solving challenging problems, innovating with cutting-edge technologies, and collaborating closely to deliver AI systems that are reliable, high-performing, and ready for production. Our team values ownership, technical excellence, and creating solutions that stand the test of scale and complexity.<div> 
Bring out your best 
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.
 
 
We win with inclusion 
SAP&rsquo;s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone &ndash; regardless of background &ndash; feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world. 
 
SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com. 
 
For SAP employees: Only permanent roles are eligible for the SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training. 
 
Qualified applicants will receive consideration for employment without regard to their age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, et al), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements. 
 
Successful candidates might be required to undergo a background verification with an external vendor.</div><div></div><div> 
AI Usage in the Recruitment Process</div><div>
For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.
</div>Please note that any violation of these guidelines may result in disqualification from the hiring process. 
 
Requisition ID: 450210 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid</div>

Tamara

<div>About Us

Tamara is the leading fintech platform in Saudi Arabia and the wider GCC region with a mission to help people make their dreams come true by building the most customer-centric financial super-app on earth. The company serves millions of users in the region and partners with leading global and regional brands such as SHEIN, Jarir, noon, IKEA and Amazon, as well as small and medium businesses.

Tamara is Saudi Arabia&rsquo;s first fintech unicorn and is backed by Sanabil Investments, a wholly owned company by the Public Investment Fund (PIF), SNB Capital, Checkout.com, amongst others. The company operates from its headquarters in Riyadh, with additional regional and global support offices.

Your Role

We are looking for a Senior Machine Learning Engineer (MLE) to join our Risk Data Science team. You will play a key role in designing, building, deploying, and scaling ML models that drive credit risk, fraud prevention, behavioral scoring, and other risk-related decision systems across our business.

You will work closely with data scientists, risk analysts, and engineering teams to transform research prototypes into high-performance, production-grade solutions that operate at scale in real-time decisioning environments.

Your Responsibilities

Model Deployment &amp; Scaling 
<ul>
<li>Productionise risk and fraud models developed by the DS team using robust, efficient, and maintainable architectures</li>
<li>Design low-latency, high-availability APIs and pipelines for real-time model inference.</li>
<li>Implement batch scoring systems for periodic risk assessments.=</li>
</ul>
MLOps &amp; Infrastructure
<ul>
<li>Build and maintain CI/CD pipelines for model deployment and monitoring.</li>
<li>Set up automated feature engineering pipelines, leveraging feature stores.</li>
<li>Ensure model governance: reproducibility, versioning, auditability, and compliance with regulatory requirements.</li>
</ul>
Model Monitoring &amp; Maintenance
<ul>
<li>Implement real-time and batch monitoring for data drift, concept drift, and model performance.</li>
<li>Build automated retraining workflows and model rollback mechanisms.</li>
</ul>
Collaboration with Risk DS
<ul>
<li>Work closely with risk data scientists to translate experimental code (Python, notebooks) into production-grade services.</li>
<li>Advise DS on efficient model architectures for operational environments.</li>
<li>Optimize feature computation for speed and scalability.</li>
</ul>
System Design &amp; Integration
<ul>
<li>Integrate models with credit underwriting, fraud detection, collections, and merchant risk systems.</li>
<li>Collaborate with backend engineering to align on API contracts and system interfaces.</li>
</ul>
Your Expertise
<ul>
<li>6+ years of experience as an MLE, ML Engineer, Mlops Developer.</li>
<li>Strong Python skills (including Pandas, NumPy, scikit-learn, PySpark, FastAPI/Flask).</li>
<li>Proficiency in distributed computing frameworks (Spark, Ray) and workflow orchestration tools (Airflow, Prefect).</li>
<li>Experience with MLOps tools (MLflow, SageMaker, Vertex AI, or similar).</li>
<li>Strong understanding of model deployment in cloud environments (AWS/GCP/Azure).</li>
<li>Solid knowledge of microservice architecture, containerization (Docker), and orchestration (Kubernetes).</li>
<li>Proven track record of deploying and maintaining ML models in production at scale.</li>
<li>Experience in building and integrating with real-time streaming systems (Kafka, Kinesis, Pub/Sub).</li>
</ul>
All qualified individuals are encouraged to apply.</div>

Intuit

<div><h2 class="jobSectionHeader">Overview</h2>
Join Intuit&rsquo;s Mid-Market AI team to help build the next generation of AI-native ERP.
Our mission is to disrupt the mid-market ERP space by replacing disparate, rigid, workflow-driven systems with intelligent, autonomous software. We are building a system of action&mdash;where data, insights, workflows are unified, continuously learning, and increasingly automated to assist mid-market operators with managing their businesses.
You will design and own AI systems that power real business actions at scale. 
Responsibilities 
<ul><li>
Discover data sources, get access to them, import them, clean them up, and make them machine learning-ready.</li><li>
Work with AI scientists to create and refine features from the underlying data and build pipelines to train and deploy models.</li><li>
Partner with AI scientists to understand, implement, refine and design machine learning and other algorithms.</li><li>
Run regular A/B tests, gather data, perform statistical analysis, draw conclusions on the impact of your models.</li><li>
Work cross functionally with product managers, AI scientists and product engineers, and communicate results to peers and leaders.</li><li>
Explore new technology shifts in order to determine how they might connect with the customer benefits we wish to deliver.</li></ul> 
Qualifications<ul><li>
Education: BS, MS, or PhD degree in Computer Science, Operations Research, Industrial Engineering, or a related field.</li><li>
Experience: 6+ years of industry experience in applied machine learning, AI engineering, or software engineering.</li><li>
Core Engineering: Strong proficiency in Python and software engineering fundamentals (data structures, algorithms, version control, CI/CD). Experience deploying highly scalable software supporting millions of users.</li><li> 
Cloud &amp; Infrastructure: Experience integrating applications with cloud technologies (i.e., AWS, GCP) and containerization (Docker/Kubernetes).</li></ul> 
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:<div>
Bay Area California $ 202,500- 274,000</div></div>

Staff Machine Learning Engineer

Capgemini

<div><div><div><div><div><div><div><h2 class="jobSectionHeader">Job Description</h2>
</div><div>The role of a machine learning professional involves applying machine learning techniques and algorithms to solve complex problems, analyze data, and develop intelligent systems.</div>
</div><div><div><h2 class="jobSectionHeader">Job Description - Grade Specific</h2>
</div><div>Plays a crucial role in driving the successful implementation of machine learning initiatives within an organization. It combines technical expertise, Machine Learning Operations Engineer enables the deployment of machine learning models into production with leadership and strategic thinking to leverage the power of machine learning for business growth and innovation.</div></div></div></div></div></div></div>

Lead Machine Learning Engineer

Unifonic

<div>
 
 Job Description
 
 
 
 Proudly voted a Great Place to Work&reg;, we are a dynamic startup in the SaaS space that is revolutionizing the way businesses communicate. Our team is made up of 500 energetic and passionate Unifones who are dedicated to delivering the best possible experience to 5000+ customer-centric companies.
 
 
 We pride ourselves on our fun and collaborative work environment, where creativity and new ideas are constantly encouraged. As shareholders in the business, we&rsquo;re so much more than a group of passionate communicators. We are Unifones. Join our team and be a part of something big!
 
 
 
 Meet the team!
 
 
 
 Our Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic&rsquo;s solutions. We work closely with other departments to ensure our products and services meet the needs of our customers. If you are passionate about technology and are excited about working on cutting-edge communication and engagement solutions, we want you on our team.
 
 
 As a Senior Machine Learning (AI) Engineer, you will be responsible for designing, developing, and deploying advanced machine learning solutions across various domains, including NLP, Text Classification, RAG, LLMs, Recommender engines, and Anomaly detection. This role involves end-to-end project ownership, from data preprocessing to the creation of service APIs, and offers opportunities to work on cutting-edge AI technologies.
 
 
 
 Help Us Shape The Future Of Communication By
 
 
 
 <ul>
 <li>
 Leading the end-to-end design, development, and deployment of robust and scalable machine learning solutions, with a strong emphasis on NLP and RAG architectures.
 </li>
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 Architecting and implementing RAG systems, combining large language models (LLMs) with robust retrieval mechanisms to improve the accuracy, factual grounding, and interpretability of generated content.
 </li>
 <li>
 Applying advanced NLP techniques for tasks such as text classification, entity recognition, sentiment analysis, summarization, question answering, and information extraction.
 </li>
 <li>
 Researching, evaluating, and integrating state-of-the-art NLP models and RAG frameworks (e.g., Transformers, BERT, GPT variants, Vector Databases, Semantic Search).
 </li>
 <li>
 Mentoring junior team members on the team, sharing knowledge, and advising the best machine learning and software engineering practices and approaches.
 </li>
 <li>
 Establishing and maintaining robust communication channels with other cross-functional teams to facilitate the integration of machine learning solutions into other Unifonic products.
 </li>
 <li>
 Developing and optimizing highly confident machine learning algorithms and models and creating/exposing the service APIs using frameworks such as Flask, FastAPIs, or other relevant frameworks.
 </li>
 <li>
 Staying up to date with the latest machine learning research papers, and AI trends (i.e. Generative AI).
 </li>
 <li>
 Collaborating with the data engineering team and other teams to collect and analyze extensive datasets, extracting insights and patterns, in real-time, near-real-time, or batch processing mode.
 </li>
 <li>
 Implementing proof of concepts and prototypes to demonstrate the potential of new AI use cases and innovations.
 </li>
 <li>
 Building scalable, maintainable machine learning services, which should handle thousands of requests per second, and help to perform the required load tests to meet the SLA.
 </li>
 <li>
 Reviewing the code of other team members and suggesting improvements to ensure the SOLID principles and clean architecture.
 </li>
 <li>
 Assisting in the project documentation and demos.
 
 
 </li>
 </ul>
 
 Job Requirements
 
 
 
 
 What you'll bring:
 
 
 
 <ul>
 <li>
 Proven experience designing and implementing RAG systems, including familiarity with various retrieval strategies (e.g., BM25, dense retrieval, hybrid approaches) and knowledge graph integration.
 </li>
 <li>
 Hands-on experience with LLM orchestration frameworks such as LangChain, LangGraph, CrewAI, or similar tools for building and managing autonomous agents.
 </li>
 <li>
 Deep expertise in various NLP techniques and models, including but not limited to:
 
 
 </li>
 </ul>
 Transformer architectures (e.g., BERT, GPT, T5, LLama, Mistral)
 
 
 Large Language Models (LLMs) and their fine-tuning/adaptation
 
 
 Vector embeddings and similarity search
 
 
 Text classification, named entity recognition (NER), sentiment analysis, summarization, and question answering.
 
 
 <ul>
 <li>
 Hands-on 3-5 years of relevant work experience as a Machine Learning Engineer.
 </li>
 <li>
 Hands-on 3+ years of experience with Python.
 </li>
 <li>
 Excellent analytical abilities, with the capacity to collect, organize, and analyze large datasets to glean valuable insights.
 </li>
 <li>
 End-to-end experience in training, evaluating, testing, and deploying machine learning products in production.
 </li>
 <li>
 Ability to write world-class code in Python (SOLID principles), considering the best software engineering fundamentals, i.e. data structures, algorithms, and data modeling
 </li>
 <li>
 Solid experience in ML frameworks such as NumPy, Pandas, Scikit-Learn, PyTorch, Keras, BERT, Tensorflow, and similar.
 </li>
 <li>
 Familiarity with MLOps best practices, e.g. Model deployment and reproducible research.
 </li>
 <li>
 Mastering data science needed skills like SQL, hypothesis testing, Data cleansing, data augmentation, data pre-processing techniques, and dimensionality reduction.
 </li>
 <li>
 Basic knowledge of Kubernetes and Docker is nice to have.
 </li>
 <li>
 Excellent understanding of Machine learning techniques like Naive Bayes classifiers, SVM, Decision Tree, KNN, K-means, Random Forest, modeling and optimization, evaluation metrics, classification, and clustering.
 </li>
 <li>
 Experience with the Hugging Face libraries (i.e. transformers).
 </li>
 <li>
 Experience fine-tuning pre-trained models and using vector search to enhance LLMs results.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques.
 </li>
 <li>
 Familiar with code versioning tools such as GIT, CI/CD concepts, and toolchains.
 </li>
 <li>
 Familiar with Agile methodologies i.e. scrum and kanban.
 </li>
 <li>
 Ability to develop high-level architecture and low-level design, End-to-end for a specific project.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is a plus.
 </li>
 <li>
 Experience with LLM frameworks (i.e. LangChain) and prompt engineering techniques is nice to have.
 </li>
 <li>
 Experience in event sourcing patterns and tools i.e. Kafka, RabbitMQ, or similar is nice to have.
 </li>
 <li>
 General knowledge of Data warehouse tools e.g. Vertica is a plus.
 </li>
 <li>
 A Bachelor&rsquo;s degree in a relevant field. (e.g. Computer Science, Computer Engineering, Software, etc).
 </li>
 <li>
 Excellent communication and collaboration skills.
 </li>
 <li>
 Good level of spoken and written Arabic and English.
 
 
 </li>
 </ul>
 
 As a Unifone you will receive a range of benefits:
 
 
 
 <ul>
 <li>
 Competitive salary and bonus.
 </li>
 <li>
 Unifonic share scheme (we are all owners!).
 </li>
 <li>
 30 holiday days after the first anniversary.
 </li>
 <li>
 Your Birthday off!
 </li>
 <li>
 Spend up to 25 days per year working from anywhere in the world!
 </li>
 <li>
 Paid leave for new parents.
 </li>
 <li>
 LinkedIn learning license.
 </li>
 </ul>
</div>

Senior Machine Learning Engineer

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