Product Engineer, Post Batch Job at Helpcare AI (San Francisco)

Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will take end-to-end ownership of the...

Location

Canada

Salary:

128000.00 - 160000.00 CAD / Year

FreshBooks

Expiration Date

Until further notice

Requirements

5+ years of experience in data science, applied ML, or ML engineering roles
Strong background in supervised and unsupervised learning, statistical modeling, and experimentation techniques
Proven experience developing and shipping ML models in production environments (batch or real-time)
Strong Python and SQL skills
comfort working with structured and unstructured data
Hands-on experience building and deploying ML or LLM-based systems (e.g. retrieval-augmented generation, embeddings, prompt tuning)
Familiarity with cloud infrastructure and ML tools, ideally on Google Cloud Platform (e.g. Vertex AI, BigQuery, Cloud Composer, Kubernetes)
Experience working with CI/CD pipelines, containerization (Docker), and job orchestration tools (Airflow, dbt, etc.)
Deep understanding of end-to-end ML operations including model observability, model drift detection, and model performance optimization
Strong communication skills and ability to explain technical concepts to non-technical stakeholders

Job Responsibility

Design, prototype, and validate machine learning models to power product features or internal tools
Own and lead all phases of the ML lifecycle from experimentation through to production deployment and model monitoring
Collaborate with Data Engineers and Product Engineers to integrate models into production infrastructure (batch and online serving)
Develop and prototype features for the shared feature store, including documentation, versioning, and consistency validation
Author high-quality, production-ready code with appropriate tests, observability, and monitoring hooks
Design experiments (e.g. A/B tests, pre-post analyses) and interpret results to guide product and business decisions
Design and build end-to-end pipelines for classification, ranking, embeddings, or generation tasks
Drive reliability practices in deployed models, including retraining logic, alerting on drift, and root cause analysis
Work closely with product and engineering stakeholders to align ML work with business priorities
Contribute to standards and documentation, mentor junior team members, and help shape our evolving ML platform

Fulltime

Data Integration Engineer

We are hiring a Senior Batch/Data Integration Engineer to design and implement b...

Location

United States , Philadelphia

Salary:

55.00 - 64.00 USD / Hour

Beacon Hill

Expiration Date

Until further notice

Requirements

5+ years of experience designing and supporting enterprise batch processing systems
Strong experience with configurable, parameter‑driven job execution and large‑scale file delivery
Proven ability to manage dependencies across multiple data platforms and teams

Job Responsibility

Enhance batch processing frameworks to support configurable data inclusion, conditional execution, and parameter‑driven output
Implement and maintain job parameters, control frameworks, and reusable batch components to support multiple downstream consumers
Design and implement output layout changes, file naming conventions, and delivery schedules in coordination with implementation teams
Collaborate with upstream and downstream engineering teams to ensure end‑to‑end integration and data consistency
Support production readiness, operational validation, and post‑deployment stability of batch workloads

Staff Software Engineer, Backend (AI Platform)

Cresta is on a mission to turn every customer conversation into a competitive ad...

Location

United States

Salary:

Not provided

Cresta

Expiration Date

Until further notice

Requirements

5+ years writing production software
2+ years focused on ML platform or infra
Expert Python (async, typing, packaging, performance)
Working Golang knowledge for systems components
Proven experience with one or more serving frameworks (e.g., vLLM, Triton, TorchServe)
Kubernetes and cloud-native ops
Solid grasp of distributed systems, networking, and container security
Culture of rigorous testing, code review, and continuous delivery

Job Responsibility

Own model serving: Design, build, and maintain low-latency, highly-available serving stacks for in-house ML model serving and integrating with LLM serving partners
Automate training pipelines: Orchestrate data prep, training, evaluation, and registry workflows on Kubernetes with solid MLOps practices
Optimize at scale: Profile and tune throughput, memory, and cost
introduce caching, sharding, batching, and GPU/CPU autoscaling where it pays off
Build platform primitives: Create reusable SDKs, templates, and CLI tools that let research and product teams ship models independently and safely
Raise the bar: Instrument deep observability (tracing, metrics, alerts), drive blameless post-mortems, and mentor engineers on production ML best practices

What we offer

Comprehensive medical, dental, and vision coverage with plans to fit you and your family
Flexible PTO to take the time you need, when you need it
Paid parental leave for all new parents welcoming a new child
Retirement savings plan to help you plan for the future
Remote work setup budget to help you create a productive home office
Monthly wellness and communication stipend to keep you connected and balanced
In-office meal program and commuter benefits provided for onsite employees

Senior Machine Learning Engineer, LLMs and Clinical NLP

We are on a mission to ensure everyone has access to medical expertise, no matte...

Location

Denmark , København

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Strong programming skills in Python and the ability to contribute to production-grade codebases
Hands-on experience with LLMs for NLP or text generation, including at least some of the following: Training, fine-tuning, or post-training transformer-based models
Building or operating LLM inference services in production, including performance work
Designing robust evaluations for generative systems, including metrics, error analysis, and human evaluation methods
Experience turning research outcomes into practical systems that can be validated and shipped
Familiarity with building ML systems beyond notebooks, such as data pipelines, CI/CD practices, monitoring, and deployment workflows
Clear communication and collaboration skills across research, engineering, and product
A Master’s degree in computer science, engineering, mathematics, statistics, physics, or a related field, or equivalent professional experience

Job Responsibility

Build and improve LLM-based clinical NLP systems, including summarization, structured extraction, and controlled generation
Train, finetune, and post-train LLMs using approaches such as supervised finetuning and preference or feedback-driven optimization where appropriate
Design evaluation strategies for clinical text generation, including offline benchmarks, human review workflows, slice-based analysis, and quality gates aligned with clinical risk
Develop and operate LLM inference services using vLLM, with focus on reliability, scalability, and practical performance
Optimize inference for latency, throughput, and cost, for example batching, caching, quantization, and decoding strategy improvements
Build and maintain APIs and services using FastAPI, and deploy and run them on Kubernetes
Take technical ownership of core NLP components, shaping best practices for model development, evaluation, and production reliability across the team, and supporting the growth of engineers working on text generation systems
Partner with researchers, engineers, and product teams to ship improvements end-to-end, including observability and monitoring to support continuous iteration

What we offer

Equipment provided by Corti

Fulltime

Senior Staff Product Manager — Apache Iceberg & Open Table Formats

The Senior Staff Product Manager for Apache Iceberg & Open Table Formats will ow...

Location

United States

Salary:

Not provided

Teradata

Expiration Date

Until further notice

Requirements

12+ years of product management experience in data infrastructure, databases, data platforms, or analytics, with a track record of shipping platform-level capabilities
Deep familiarity with Apache Iceberg or comparable open table formats (Apache Hudi, Delta Lake), including understanding of metadata design, catalog architecture, and query optimization
Demonstrated experience in open-source community engagement—contributing to or leading initiatives within Apache Software Foundation projects or similar open-source ecosystems
Strong technical fluency in lakehouse architecture, including concepts like ACID transactions on object storage, schema evolution, partition evolution, snapshot isolation, and compute-storage separation
Proven ability to lead cross-functional teams across engineering, developer relations, and go-to-market functions
Hands-on experience developing agentic AI systems and successfully bringing agent-driven solutions from concept to market
Foundational AI skills and the ability to understand how AI can be applied to improve outcomes in your area of expertise

Job Responsibility

Serve as Teradata’s primary representative and advocate within the Apache Iceberg open-source community, building trust and credibility with contributors, committers, and the Apache Software Foundation (ASF)
Develop and execute a developer community strategy that grows Teradata’s mindshare among data engineers, lakehouse architects, and open-source contributors working with Apache Iceberg
Build and nurture relationships with the Apache Software Foundation, including participation in Iceberg PMC discussions, contributing to project governance, and representing Teradata’s interests in community roadmap decisions
Drive external thought leadership through conference talks (e.g., ApacheCon, Data + AI Summit, Subsurface), blog posts, technical papers, and social media engagement on Iceberg-related topics
Collaborate with partners and ecosystem vendors (e.g., cloud providers, compute engine vendors, catalog providers) to ensure Teradata’s Iceberg implementation is interoperable and well-positioned in the broader lakehouse ecosystem
Create and maintain developer-facing content including tutorials, reference architectures, and best-practice guides for using Iceberg with Teradata
Own the product roadmap for Iceberg integration within the Teradata platform, covering Iceberg read/write operations, catalog interoperability, metadata management, schema evolution, and partition optimization
Partner closely with database engineering teams to identify and drive performance improvements for Iceberg workloads, including query planning, predicate pushdown, data skipping, compaction, and table maintenance operations
Define product requirements for Iceberg-native capabilities such as time travel, snapshot isolation, branching and tagging, and hidden partitioning within the Teradata ecosystem
Conduct competitive analysis of Iceberg implementations across the industry (e.g., Snowflake, Databricks, Dremio, Cloudera) and translate insights into prioritized product investments

What we offer

We prioritize a people-first culture
We embrace a flexible work model
We focus on well-being
We are an anti-racist company
We foster an equitable environment that celebrates people for all of who they are

Fulltime

Senior Software Engineer, ML Platform

We’re looking for a software engineer to join Parafin’s Infrastructure team and ...

Location

United States , San Francisco

Salary:

230000.00 - 265000.00 USD / Year

Parafin

Expiration Date

Until further notice

Requirements

5+ years of software engineering experience, including experience on ML platform/MLOps systems (training, deployment, and/or feature pipelines)
Strong Python
solid software design and testing fundamentals
Proficiency with SQL
hands-on Spark/PySpark experience
Knowledge of ML fundamentals—probability & statistics, supervised vs. unsupervised learning, bias/variance & regularization, feature engineering, model evaluation metrics, validation strategies, and production concerns like drift, stability, and monitoring
Expertise with modern data/ML stacks—AWS, Databricks (workflows, lakehouse, MLflow/registry, Model Serving), and Airflow (or equivalent orchestration)
Experience building real-time systems (service design, caching, rate limiting, backpressure) and batch pipelines at scale
Practical knowledge of feature-store concepts (offline/online stores, backfills, point-in-time correctness), model registries, experiment tracking, and evaluation frameworks
Strong problem-solving skills and a proactive attitude toward ownership and platform health

Job Responsibility

Turn notebooks into software
Decompose data scientist training/inference notebooks into reusable, tested components (libraries, pipelines, templates) with clear interfaces and documentation
Create developer-friendly ML abstractions
Build SDKs, CLIs, and templates that make it simple to define features, train/evaluate models, and deploy to batch or real-time targets with minimal boilerplate
Build our real-time ML inference platform
Stand up and scale low-latency model serving
Expand batch ML inference
Improve scheduling, parallelism, cost controls, observability, and failure/rollback for large-scale batch scoring and post-processing
Own and expand the feature store
Design offline/online feature definitions, high read/write throughput, and consistent offline/online semantics

What we offer

Equity grant
Medical, dental & vision insurance
Work from home flexibility
Unlimited PTO
Commuter benefits
Free lunches
Paid parental leave
401(k)
Employee assistance program

Fulltime

Senior Software Engineer

Collaborate with backend, product, and quality engineering teams to build and de...

Location

United States , Oakland

Salary:

213600.00 - 215000.00 USD / Year

SiriusXM

Expiration Date

Until further notice

Requirements

Master’s degree in Computer Science, Data Science or Engineering (Computer or Electrical), plus two years of experience in the position offered or as Software Developer or Software/Systems Engineer
Bachelor’s degree in Computer Science, Data Science or Engineering (Computer or Electrical), plus five years of progressive post-Bachelor’s experience in the position offered or as Software Developer or Software/Systems Engineer
contributing to detailed project design and ensuring alignment with project objectives and client requirements across all phases of the Software Development Life Cycle (SDLC)
communicating with business stakeholders and refining their requests into technical specifications
developing back-end applications with Soap architecture
applying system design and object-oriented design concepts
programming in Java and working with SQL distributed databases
applying continuous integration and testing into the development process
developing robust web service modules within Enterprise applications using RAD (Rapid Application Development), leveraging industry-leading tools and methodologies
implementing database functions, procedures, and triggers, enhancing data management capabilities and ensuring optimal performance

Job Responsibility

Collaborate with backend, product, and quality engineering teams to build and deliver data products for stakeholders
Work with large, complex datasets and translate functional business requirements into scalable, high-quality engineering solutions
Design, implement, and optimize data pipelines to support both real-time and batch processing workflows
Develop and maintain high-performance, distributed databases to support analytics and data applications
Evaluate and integrate emerging technologies and tools that enhance data engineering efficiency and system reliability
Create and maintain technical documentation covering architecture, data lineage, and engineering standards
Lead root-cause analysis and resolution of data issues, driving long-term fixes and preventative measures
Actively participate in sprint planning, code reviews, and technical design discussions to ensure quality and architectural alignment

Fulltime

GTM Engineer – CRM & Integrations

This is the CRM and integrations engineering role on our GTM Engineering team. A...

Location

India , Gurugram

Salary:

Not provided

Coralogix

Expiration Date

Until further notice

Requirements

5–8+ years of hands-on Salesforce development experience in Sales Cloud and complex multi-cloud environments
CPQ implementation experience strongly preferred — Nue.io, Salesforce CPQ, DealHub, or similar
willingness to develop deep Nue.io expertise rapidly is a must
Strong production Apex experience: trigger frameworks, separation-of-concerns patterns, bulkification, governor limit management
Experience building LWC components and front-end Salesforce interfaces
Hands-on REST/SOAP integration experience including Named Credentials, OAuth, and middleware orchestration
Strong understanding of Salesforce data model, sharing model, and security architecture
Experience with SFDX, Git-based workflows, and CI/CD deployment pipelines (Copado, Gearset, or GitHub Actions)
Experience working with Salesforce APIs (Bulk API, Streaming API, Metadata API) for cross-system integrations
Exposure to AI-assisted development tools and automation orchestration platforms a plus

Job Responsibility

Implement Nue.io CPQ as the primary builder — configuring and engineering product catalog, pricing rules, discount frameworks, quoting workflows, and approval processes
Build Nue.io integrations with Salesforce CRM, DocuSign CLM, billing systems, and finance/ERP stack
Develop quoting automation, contract generation, and order management workflows
Partner with Finance and Revenue Operations to encode pricing logic and deal structure rules into the CPQ system
Own post-go-live CPQ maintenance and iteration as the revenue model evolves
Implement scalable Salesforce automation and custom logic aligned with architectural standards set by the Salesforce Architect
Write production-grade Apex code including trigger frameworks, batch jobs, queueable processes, and platform events
Build and maintain Lightning Web Components (LWC) for internal GTM tool interfaces
Design and maintain complex object models, data relationships, permission structures, and sharing models
Support sandbox management, structured deployments, and CI/CD processes

Fulltime

Product Engineer, Post Batch

Helpcare AI

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

Job Description:

Job Responsibility:

Requirements:

Nice to have:

Additional Information:

Job Posted:
December 31, 2025

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