Senior Product Manager, AI & ML Platform Job at Spring Health (New York)

Senior Product Manager - AI

We are seeking an experienced Senior Product Manager to join our Product team in...

Location

India , Chennai

Salary:

Not provided

Arcadia

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in engineering or business management from top universities
6+ years of overall experience in software product management in SaaS or data/platform product companies
At least 4+ years of direct & hands-on PM experience
Experience building enterprise-grade B2B software products, ideally with notable technical data complexity and a focus on AI/ML applications
Proven experience working with AI technologies, including LLMs or ML models, to create products
At least one experience in building out agents or similar agentic / automation pipelines
A natural curiosity to continuously evolve with AI developments within the industry
Experience working with globally distributed teams in multiple timezone environments
Strong expertise with internal tools and systems in a medium to large enterprise and building complex systems around automation
Demonstrated experience aligning and influencing cross-functional teams and diverse stakeholders

Job Responsibility

Create and own the product roadmap for the AI Data Pipeline squad aligning to the overall business and product strategy that helps build and scale Arcadia’s energy data and AI products
Define, prioritize, and build product initiatives and features that improve the scale, quality, and reliability of the data systems, tools, and applications
Lead the AI Data Pipeline product squad to tackle utility data acquisition, extraction and enrichment challenges faced by internal teams
Champion (and model) AI tool usage (e.g., Gemini, Cursor) to drive productivity improvements both in product management and with your engineering team
Work with data science and other AI team members to design agentic features, prompts, and pipelines (e.g., RAG, MCPs)
Drive technical learning and innovation by self-learning new technology stacks (AI, Snowflake, etc.) and working with engineering to rapidly build and prototype solutions
Write clear and detailed product requirements that can be easily understood by technical and non-technical audiences
Collaborate cross-functionally with peers in Engineering, Operations, and Data Science to deliver products on time
Constantly monitor and update on the progress of the initiatives to all the relevant stakeholders and the leadership team
Balance long-term bets with short-term improvements, optimizing for speed of learning and time to impact

What we offer

Competitive compensation based on market standards
Flexible Leave Policy
Office located in the heart of the city in case you need to step in for any purpose
Medical Insurance (1+5 Family Members)
Flexible Benefit Plan
Awards and Bonus
Annual performance cycle
Quarterly engagement activities
A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency

Fulltime

AI Product Manager

We’re scaling AI and machine learning across our products, devices, and operatio...

Location

United States , Boston

Salary:

121300.00 - 177900.00 USD / Year

SimpliSafe

Expiration Date

Until further notice

Requirements

8+ years of product management experience, including significant ownership of AI/ML or data-intensive products
Clear track record of shipping production ML systems (not just integrating third-party AI APIs), in close partnership with data science, ML engineering, and MLOps
Principal-level impact: leading cross-team initiatives, shaping strategy, and influencing senior stakeholders
Strong understanding of core ML concepts and lifecycle: data, labeling, training/validation, evaluation metrics, deployment, monitoring, and retraining
ML experience with at least one of following: computer vision or sensor data, LLM-powered applications (prompting, RAG, fine-tuning, evaluation) and/or hardware or edge products (e.g., on-device models, connectivity/latency trade-offs)
Familiarity with modern ML infrastructure (cloud platforms, model serving, CI/CD for ML, monitoring/alerting)
Comfortable going deep into data, metrics, and model behavior—not just the UX layer
Excellent communicator who can make complex AI topics clear to diverse audiences
Strong alignment with our values: customer-obsessed, low ego, highly collaborative, comfortable with ambiguity, and biased toward learning and iteration.

Job Responsibility

Define and communicate the multi-year roadmap for key AI/ML capabilities across SimpliSafe
Identify and prioritize AI opportunities where models and data can materially improve safety, customer experience, or efficiency—on both devices and cloud services
Make build-vs-buy decisions for AI capabilities in partnership with data science and engineering
Partner with data scientists, ML engineers, and MLOps to design and deliver end-to-end ML solutions—from problem framing through data, training, evaluation, deployment, and monitoring
Work with hardware and embedded teams to shape edge AI/ML experiences (e.g., on-device detection, low-latency decisions, bandwidth-aware designs)
Define model-level requirements (metrics, latency, cost, guardrails) and connect them to business outcomes (e.g., false alarm reduction, detection accuracy, handle time, CSAT)
Translate product needs into requirements for ML platform capabilities (model serving, observability, experiment tracking, human-in-the-loop tools)
Lead product direction for LLM and multimodal use cases (e.g., text, vision, sensor data)
Decide when to use prompt engineering, RAG, fine-tuning, or traditional ML—and how to evaluate quality, safety, and hallucinations
Design workflows that incorporate human review and escalation where needed

What we offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow, and thrive
A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families
Free SimpliSafe system and professional monitoring for your home
Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change
Participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits.

Fulltime

Senior Principal Technical Program Manager - ML Platform

Location

Salary:

231300.00 - 301975.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

8+ years of experience on software teams as Development Manager, Technical Product Manager or TPM leading technical platforms areas
Deep domain experience in AI and/or Search. Example: Model Inference, Model Evaluation, Model Training, LLM Ops, Semantic Search, Search Relevance, etc.
Partner with Engineering in defining direction, strategy and execution at Platform level
Strategic thinking and ability to understand business objectives to translate them into technical problems and programs.
Technical understanding of systems involved. Willingness to develop domain expertise in the area they operate - storage, networking, authentication, capacity management, service deployments, etc.
TPMs are not expected to write or read code, but are expected to understand system flows, block architectures, APIs and such.
Experience defining and running end-to-end complex technical programs
Strong leadership, organizational, and communication skills

Job Responsibility

Understand and stay up-to-date on latest innovations in AI and Search. Partner closely with engineering teams to translate these into practical platform evolution for Atlassian bringing value to our customers.
Analyze business objectives, customer needs, product adoption inhibitors and opportunities, industry trends, and based on these, in close collaboration with your stakeholders, define a long-term strategy and roadmap for your platform and product components.
Understand business objectives and translate them into technical systems problems that need to be prioritized solved in the current business environment.
Define specific systems programs and create a plan of action for realizing those programs. Such programs could be around capacity planning, migration efforts, high availability, network architecture, performance optimization, reliability improvements and more.
Use your technical understanding of Atlassian and related systems to partner with and influence engineers and architects in making progress on these problems.
Responsible for taking a systematic approach to engineering problems. This includes: prioritizing tasks, scoping out the project, defining objectives, and making consistent progress against each of these.
Be accountable for the success of these technical programs by managing the entire lifecycle from initiation to forecasting, budgeting, scheduling, etc.
Manage complex dependencies and projects with a broad scope across the company

What we offer

health and wellbeing resources
paid volunteer days

Senior Engineering Manager - AI

We are seeking a Senior Engineering Manager (Level 5) to lead a high-performing ...

Location

India , Chennai

Salary:

Not provided

Arcadia

Expiration Date

Until further notice

Requirements

15+ years of professional experience in software engineering
At least 4+ years in engineering leadership roles
Strong technical background in AI/ML systems, large-scale data pipelines, and cloud-native platforms
Hands-on experience with Python (preferred), modern ML frameworks (PyTorch/TensorFlow), and cloud services (AWS)
Proven success in managing teams of 4–6 engineers, scaling processes, and building diverse, high-performance teams
Strong architectural design and system-thinking abilities
Excellent communication skills with ability to influence cross-functional stakeholders
Passion for sustainability, decarbonization, and using technology to create positive climate impact
Experienced with building agentic pipelines with the latest models from Anthropic, Google, OpenAI, and more

Job Responsibility

Lead and grow a team of engineers focused on building AI-driven and data-intensive systems for the Arcadia platform
Design and train ML/AI models (forecasting, NLP, graph learning, generative AI) to improve data quality, cost effectiveness, and system scalability
Build true agentic workflows with multi-step processing incorporating RAG pipelines and MCPs
Balance management responsibilities (hiring, coaching, performance reviews, career growth) with technical leadership (architecture, system design, technical strategy)
Drive end-to-end delivery of complex projects in partnership with Product, Data, and Infrastructure teams
Guide the adoption of modern AI/ML technologies, ensuring practical, scalable use in production
Foster a culture of high performance, ownership, and technical excellence
Establish engineering best practices in testing, observability, reliability, and CI/CD
Partner with leadership to define roadmaps, set priorities, and align execution with Arcadia’s strategic goals
Represent AI across the company, articulating technical trade-offs and championing innovation

What we offer

Competitive compensation and employee stock options
Hybrid/remote-first working model (India-based role, with global collaboration)
Flexible leave policy
Comprehensive medical insurance (self + family members)
Annual performance cycle + quarterly recognition awards
A supportive, diverse engineering culture grounded in empathy, teamwork, and innovation

Fulltime

Senior ML Platform Engineer

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP e...

Location

United States , Boston

Salary:

150000.00 - 210000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field
or equivalent practical experience
5+ years of experience in software engineering with a focus on ML infrastructure, cloud platforms, or MLOps
Strong programming skills in Python, with experience in building distributed systems and REST/gRPC APIs
Deep knowledge of cloud-native services and infrastructure-as-code (e.g., AWS CDK, Terraform, CloudFormation)
Hands-on experience with model deployment platforms such as AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks
Proficiency in ML lifecycle tools (MLflow, Weights & Biases, BentoML) and containerization strategies (Docker, Kubernetes)
Understanding of data engineering and ingestion pipelines, with ability to interface with data lakes, feature stores, and streaming systems
Proven ability to work cross-functionally with Data Science, Data Platform, and Software Engineering teams, influencing decisions and driving alignment
Passion for AI and automation to solve real-world problems and improve operational workflows

Job Responsibility

Architect, build, own, and operate scalable ML infrastructure in cloud environments (e.g., AWS), optimizing for speed, observability, cost, and reproducibility
Create, support, and maintain core MLOps infrastructure (e.g., MLflow, feature store, experiment tracking, model registry), ensuring reliability, scalability, and long-term sustainability
Develop, evolve, and operate MLOps platforms and frameworks that standardize model deployment, versioning, drift detection, and lifecycle management at scale
Implement and continuously maintain end-to-end CI/CD pipelines for ML models using orchestration tools (e.g., Prefect, Airflow, Argo Workflows), ensuring robust testing, reproducibility, and traceability
Partner closely with Data Science, Sensor Intelligence, and Data Platform teams to operationalize and support model development, deployment, and monitoring workflows
Build, manage, and maintain both real-time and batch inference infrastructure, supporting diverse use cases from physiological analytics to personalized feedback loops for WHOOP members
Design, implement, and own automated observability tooling (e.g., for model latency, data drift, accuracy degradation), integrating metrics, logging, and alerting with existing platforms
Leverage AI-powered tools and automation to reduce operational overhead, enhance developer productivity, and accelerate model release cycles
Contribute to and maintain internal platform documentation, SDKs, and training materials, enabling self-service capabilities for model deployment and experimentation
Continuously evaluate and integrate emerging technologies and deployment strategies, influencing WHOOP’s roadmap for AI-driven platform efficiency, reliability, and scale

What we offer

equity
benefits

Fulltime

Senior AI ML Engineer

We are seeking a highly skilled and experienced Assistant Vice President (AVP), ...

Location

India , Pune

Salary:

Not provided

Citi

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field
Minimum of 6+ years of professional experience in Data Science, Machine Learning Engineering, or a similar role, with a strong track record of deploying ML models to production
Proven experience in a lead or senior technical role
Expert-level proficiency in Python programming, including experience with relevant data science libraries (e.g., Pandas, NumPy, Scikit-learn) and deep learning frameworks (e.g., TensorFlow, PyTorch)
Strong hands-on experience designing, developing, and deploying RESTful APIs using FastAPI
Solid understanding and practical experience with CI/CD tools and methodologies (e.g., Jenkins, GitLab CI, GitHub Actions, Azure DevOps) for MLOps
Experience with MLOps platforms, model monitoring, and model versioning
Experience with at least one major cloud provider (e.g., AWS, Azure, GCP) for deploying and managing ML workloads
Proficiency in SQL and experience working with relational and/or NoSQL databases
Deep understanding of machine learning algorithms, statistical modeling, and data mining techniques

Job Responsibility

Design, develop, and implement advanced machine learning models (e.g., predictive, prescriptive, generative AI) to solve complex business problems, from initial data exploration and feature engineering to model training and evaluation
Lead the deployment of AI/ML models into production environments, ensuring scalability, reliability, and performance
Build and maintain robust, high-performance APIs (using frameworks like FastAPI) to serve machine learning models and integrate them with existing applications and systems
Establish and manage continuous integration and continuous deployment (CI/CD) pipelines for ML code and model deployments, promoting automation and efficiency
Collaborate with data engineers to ensure optimal data pipelines and data quality for model development and deployment
Conduct rigorous experimentation, A/B testing, and model performance monitoring to continuously improve and optimize AI/ML solutions
Promote and enforce best practices in software development, including clean code, unit testing, documentation, and version control
Mentor junior team members, contribute to technical discussions, and drive the adoption of new technologies and methodologies within the team
Effectively communicate complex technical concepts and model results to both technical and non-technical stakeholders.

What we offer

Not explicitly stated.

Fulltime

Senior Platform Engineer, ML Data Systems

We’re looking for an ML Data Engineer to evolve our eval dataset tools to meet t...

Location

United States , Mountain View

Salary:

137871.00 - 172339.00 USD / Year

Khan Academy

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
5 years of Software Engineering experience with 3+ of those years working with large ML datasets, especially those in open-source repositories such as Hugging Face
Strong programming skills in Go, Python, SQL, and at least one data pipeline framework (e.g., Airflow, Dagster, Prefect)
Experience with data versioning tools (e.g., DVC, LakeFS) and cloud storage systems
Familiarity with machine learning workflows — from training data preparation to evaluation
Familiarity with the architecture and operation of large language models, and a nuanced understanding of their capabilities and limitations
Attention to detail and an obsession with data quality and reproducibility
Motivated by the Khan Academy mission “to provide a free world-class education for anyone, anywhere.”
Proven cross-cultural competency skills demonstrating self-awareness, awareness of other, and the ability to adopt inclusive perspectives, attitudes, and behaviors to drive inclusion and belonging throughout the organization.

Job Responsibility

Evolve and maintain pipelines for transforming raw trace data into ML-ready datasets
Clean, normalize, and enrich data while preserving semantic meaning and consistency
Prepare and format datasets for human labeling, and integrate results into ML datasets
Develop and maintain scalable ETL pipelines using Airflow, DBT, Go, and Python running on GCP
Implement automated tests and validation to detect data drift or labeling inconsistencies
Collaborate with AI engineers, platform developers, and product teams to define data strategies in support of continuously improving the quality of Khan’s AI-based tutoring
Contribute to shared tools and documentation for dataset management and AI evaluation
Inform our data governance strategies for proper data retention, PII controls/scrubbing, and isolation of particularly sensitive data such as offensive test imagery.

What we offer

Competitive salaries
Ample paid time off as needed
8 pre-scheduled Wellness Days in 2026 occurring on a Monday or a Friday for a 3-day weekend boost
Remote-first culture - that caters to your time zone, with open flexibility as needed, at times
Generous parental leave
An exceptional team that trusts you and gives you the freedom to do your best
The chance to put your talents towards a deeply meaningful mission and the opportunity to work on high-impact products that are already defining the future of education
Opportunities to connect through affinity, ally, and social groups
401(k) + 4% matching & comprehensive insurance, including medical, dental, vision, and life.

Fulltime

Senior Machine Learning Engineering Manager, Gen AI

We're seeking a Senior Machine Learning Manager (M60) to lead a cross-functional...

Location

United States

Salary:

193500.00 - 303150.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

8+ years in ML, search, or backend engineering roles, with 3+ years leading teams
Strong track record of shipping ML-powered or LLM-integrated user-facing products
Experience with RAG systems (vector search, hybrid retrieval, LLM orchestration)
Deep experience in either modeling (e.g., LLMs, search, NLP) or engineering (e.g., backend infra, full-stack), with the ability to lead end-to-end
Deep understanding of LLM ecosystems (OpenAI, Claude, Mistral, OSS), orchestration frameworks (LangChain, LlamaIndex), and vector databases (Weaviate, Pinecone, FAISS, etc.)
Strong product intuition and ability to translate complex tech into valuable user features
Familiarity with GenAI evaluation methods: hallucination detection, groundedness scoring, and human-in-the-loop feedback loops
Master’s or PhD in Computer Science, Machine Learning, or related field preferred—or equivalent practical experience

Job Responsibility

Lead the vision, design, and execution of LLM-powered AI products, leveraging advance AI modeling (e.g. SLM post-training/fine-tuning), RAG architectures and hybrid ranking system
Define system architecture across retrievers, rankers, orchestration layers, prompt templates, and feedback mechanisms
Work closely with product and design teams to ensure delightful, fast, and grounded user experiences
Build and manage a cross-disciplinary team including ML engineers, backend/frontend engineers, and applied scientists
Foster a culture of E2E ownership — empowering the team to move from prototype to production quickly and iteratively
Mentor individuals to grow in both technical depth and product acumen
Shape the technical roadmap and long-term strategy for GenAI search across Atlassian’s product suite
Partner with platform and infra teams to scale inference, evaluate performance, and integrate usage signals for continuous improvement
Champion data quality, grounding, and responsible AI practices in all deployed features

What we offer

health and wellbeing resources
paid volunteer days

Fulltime

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Senior Product Manager, AI & ML Platform

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