Senior Machine Learning Engineer

At Cresta, we are dedicated to building state-of-the-art Machine Learning system...

Location

United States; Canada

Salary:

Not provided

Cresta

Expiration Date

Until further notice

Requirements

Master’s or Ph.D. in Computer Science, Machine Learning, AI, or a related field
5+ years of hands-on experience building and deploying ML models in production
Strong knowledge of ML frameworks and NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face, spaCy, NLTK)
Solid experience with modern ML techniques including transformer architectures, embeddings, retrieval systems, and large-scale model training
Experience designing and deploying Retrieval-Augmented Generation pipelines for enterprise use cases
Familiarity with evaluation and benchmarking frameworks for ML/LLM models
Strong passion for AI-driven innovation, with a proven ability to deliver impactful, production-grade solutions

Job Responsibility

Build and optimize agentic AI workflows that enable users to dynamically interact with and refine outputs from ML systems
Research and implement advanced ML and NLP techniques, including transformer-based models, embeddings, and retrieval-augmented generation
Develop evaluation frameworks to assess accuracy, robustness, and usability of ML/LLM models in production environments
Design, train, and deploy machine learning models for tasks such as classification, entity identification, information extraction, retrieval, topic discovery, and structured insight generation
Architect and optimize RAG pipelines for grounding LLMs with enterprise data to ensure accuracy and reliability
Collaborate with engineers, UX designers, and product managers to integrate AI-driven capabilities into Cresta’s platform
Optimize ML pipelines and data processing systems to operate efficiently at scale

What we offer

We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
Paid parental leave to support you and your family
Monthly Health & Wellness allowance
Work from home office stipend to help you succeed in a remote environment
Lunch reimbursement for in-office employees
PTO: 3 weeks in Canada
Compensation for this position includes a base salary, equity, and a variety of benefits

Fulltime

Senior Machine Learning Engineer

Machine Learning is a cornerstone at Taskrabbit, and we're looking for a seasone...

Location

United States , New York; San Francisco

Salary:

148000.00 - 200000.00 USD / Year

Taskrabbit

Expiration Date

Until further notice

Requirements

BS, MS, or PhD in Computer Science, Statistics, Operations Research, or a related quantitative field
3+ years of industry experience building and deploying high-quality, production-grade machine learning models and systems
Strong theoretical knowledge and hands-on experience in machine learning, particularly in areas like search, ranking, recommender systems, or NLP
Solid software engineering skills with proficiency in one or more programming languages, including Python
Experience with popular ML libraries like Scikit-learn, lightgbm, xgboost, TensorFlow, PyTorch, etc.
Proficiency in SQL is also required for writing complex queries and transforming data
Experience building REST API-based services
Experience with modern data and ML technologies, such as Docker, Kubernetes, Kafka, Airflow, data warehouses (eg snowflake, redshift or BigQuery), and data lakes
Excellent communication skills, with the ability to present complex findings and recommendations clearly to both technical and non-technical audiences
A passion for quickly learning new technologies and a drive to solve challenging problems

Job Responsibility

Model Development & Research: Research, design, and implement machine learning models to solve key business problems in areas like search ranking, recommendations, and content discovery
End-to-End ML Lifecycle: Own the entire lifecycle of ML models, including feature engineering, training, evaluation, deployment, and monitoring
Infrastructure & Scalability: Build scalable and reliable ML infrastructure and data pipelines that support reproducible feature engineering and machine learning model deployment in real-time, near real-time, and batch processes
Performance & Quality: Build monitoring services to understand data quality and model performance of complex systems, and collaborate with engineering and science teams to optimize existing algorithms for training and evaluation
Software Engineering Excellence: Independently solve complex problems, write clean, efficient, and sustainable code, and actively participate in code reviews, documentation, and the full software engineering lifecycle

What we offer

Taskrabbit is a Hybrid Company
The People
The Diverse Culture
Taskrabbit offers our employees with employer-paid health insurance and a 401k match with immediate vesting for our US based employees
We offer all of our global employees generous and flexible time off with 2 company-wide closure weeks, Taskrabbit product stipends, wellness + productivity + education stipends, IKEA discounts, reproductive health support, and more

Fulltime

Solutions Engineer

As a Solutions Engineer at Encord, you will be the core technical expert and pro...

Location

United Kingdom , London

Salary:

Not provided

Encord

Expiration Date

Until further notice

Requirements

2-3+ years of experience in a customer-facing role within an AI business, such as Solutions Engineering, Solutions Architecture, or Technical Account Management
Expert-level proficiency in Python is a must
Excellent communication and presentation skills
Strong technical command of modern cloud infrastructure (GCP, AWS, Azure) and machine learning concepts
A 'hacker mindset' with a strong engineering foundation
A solution-driven and customer-obsessed mindset
Ability to translate value between technical and commercial stakeholders

Job Responsibility

Partner with Account Executives and the ML team to lead the technical strategy for complex, enterprise sales cycles and co-own the technical win
Lead deep technical discovery sessions with a wide range of stakeholders to not only uncover business pain but to architect a complete technical solution and integration path
Architect, build, and deliver highly-technical, customized product demonstrations and proof-of-concepts (POCs) that solve specific, complex customer problems
Own the end-to-end technical implementation of POCs, writing robust, production-quality Python scripts for complex data ingestion, pre/post-processing, dataset management, and custom platform integrations
Act as the key technical advisor to prospects, expertly guiding them through security, architecture, and integration evaluations, particularly on complex data pipelines involving multimodal data, LiDAR, or robotics sensor data
Translate complex technical architectures and findings into clear, persuasive value propositions for senior, non-technical stakeholders (Directors, VPs, CTOs)
Serve as the 'voice of the customer' to our Product and Engineering teams, channeling detailed, technical feedback from complex enterprise clients to help shape the product roadmap

What we offer

Competitive salary and equity in a hyper growth business
Strong in-person culture
Room to grow into anything you choose to
25 days annual leave a year + public holidays

Fulltime

Sr. Delivery Solutions Architect

At Databricks we are on a mission to empower our customers to solve the world's ...

Location

South Korea , Seoul

Salary:

Not provided

databricks

Expiration Date

Until further notice

Requirements

8+ years in a customer-facing pre-sales, technical architecture, customer success, or consulting role
Experience understanding architecture related distributed data systems, specifically within one of the following: Data Engineering technologies (e.g. Spark, Hadoop, Kafka)
Data Warehousing (e.g. SQL, OLTP/OLAP/DSS)
Data Science and Machine Learning technologies (e.g. pandas, scikit-learn, HPO)
Comfortable managing multiple projects at once, and engaging a virtual team of subject matter experts
Influencing and leading teams - especially without having direct reporting line responsibility
Executive Stakeholder management - experience in effectively engaging and influencing a variety of audiences at all levels of an organization with particular success in building and maintaing strong CxO level relationship
Executive escalation management - experience in resolving complex and critical escalation with senior customer and internal executives
Strategic Management Consulting - experience of conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis and managing delivery of complex programmes/projects
Building and steering to a value case - business value consulting and realization

Job Responsibility

Engage with the Solutions Architect to understand the full Use Case Demand Plan for prioritized customers
Own the Post-Technical Win technical account strategy and investment plan for the majority of Databricks Use Cases within our most strategic accounts
Be the accountable technical leader assigned to specific Use Cases and customer(s) across multiple selling teams and internal stakeholders, creating certainty from uncertainty/ambiguity and driving onboarding, enablement, success, go-live and healthy consumption of the workloads where the customer has made the decision to consume Databricks
Be the first point of contact for any technical issues or questions related to production/go live status of agreed upon Use Cases within an account
Leverage both Shared Services of User Education, Onboarding/Technical Services and Support resources, along with escalating to Level 400/500 technical experts to execute on the right tasks that are beyond your scope of activities or expertise
Create, own and execute a PoV as to how key use cases can be accelerated into production, bringing EM/PM in to prepare Professional Services proposals
Navigate Databricks Product and Engineering teams for New Product Innovations, Private Previews and Upgrade needs
Build and maintain an executive level as well as a detailed programme level success plan that covers all activities of Customer, PS, Partner, SSA, Product Specialist, SA
Proactively provide internal and external updates - KPI reporting on the status of consumption and customer health, covering investment status, key risks, product adoption and use case progression - to your Technical GM
Development of reusable and scalable assets and mentorship of junior team members to establish the DSA team

AI & Data Lead

We are seeking a highly skilled AI & Data Lead to spearhead our transformation i...

Location

United Kingdom , North West

Salary:

Not provided

Dynamic Search Solutions

Expiration Date

Until further notice

Requirements

Proven experience in a senior data/AI/analytics role (e.g., Data Lead, Analytics Lead, AI Specialist, BI Lead)
Strong background with Power BI, including DAX, modelling, governance, and enterprise deployments
Hands-on experience building AI and machine learning solutions using modern cloud tools (Azure preferred)
Strong understanding of data engineering concepts (ETL/ELT, pipelines, warehousing)
Ability to translate business challenges into technical AI/analytics solutions
Excellent stakeholder engagement and communication skills
Strategic thinker capable of setting direction and driving organisational change

Job Responsibility

Strategic Leadership & Planning Develop and own the company’s AI, analytics, and data strategy
Create a roadmap for moving from traditional BI to a modern, AI-augmented data ecosystem
Identify opportunities where AI, ML, and automation can drive measurable value
Act as a trusted advisor to senior leaders and departments regarding data, BI, and AI
Translate complex data and AI concepts into clear business language and use cases
Facilitate workshops, run discovery sessions, and guide teams on AI best practices
Build prototypes and production-level AI/ML solutions, such as predictive models, natural language interfaces, and automation workflows
Develop robust data models, pipelines, and integrations to ensure scalable AI adoption
Establish data governance standards, security controls, and compliance practices
Own data quality frameworks to ensure trusted reporting and model reliability

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